WorldWideScience

Sample records for ontology recognition semantic

  1. Ontology-Based Semantic Cache in AOKB

    Institute of Scientific and Technical Information of China (English)

    郑红; 陆汝钤; 金芝; 胡思康

    2002-01-01

    When querying on a large-scale knowledge base, a major technique of im-proving performance is to preload knowledge to minimize the number of roundtrips to theknowledge base. In this paper, an ontology-based semantic cache is proposed for an agentand ontology-oriented knowledge base (AOKB). In AOKB, an ontology is the collection of re-lationships between a group of knowledge units (agents and/or other sub-ontologies). Whenloading some agent A, its relationships with other knowledge units are examined, and thosewho have a tight semantic tie with A will be preloaded at the same time, including agents andsub-ontologies in the same ontology where A is. The preloaded agents and ontologies are savedat a semantic cache located in the memory. Test results show that up to 50% reduction inrunning time is achieved.

  2. Integrated Semantic Similarity Model Based on Ontology

    Institute of Scientific and Technical Information of China (English)

    LIU Ya-Jun; ZHAO Yun

    2004-01-01

    To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper.With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user's question and answers in knowlegdge base.The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology.More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached.The result is very satisfied.

  3. SEMANTIC TERM BASED INFORMATION RETRIEVAL USING ONTOLOGY

    Directory of Open Access Journals (Sweden)

    J. Mannar Mannan

    2014-01-01

    Full Text Available Information Searching and retrieval is a challenging task in the traditional keyword based textual information retrieval system. In the growing information age, adding huge data every day the searching problem also augmented. Keyword based retrieval system returns bulk of junk document irrelevant to query. To address the limitations, this paper proposed query terms along with semantic terms for information retrieval using multiple ontology reference. User query sometimes reflects multiple domain of interest that persist us to collect semantically related ontologies. If no related ontology exists then WordNet ontology used to retrieve semantic terms related to query term. In this approach, classes on the ontology derived as semantic related text keywords, these keywords considered for rank the documents.

  4. Semantic similarity between ontologies at different scales

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qingpeng; Haglin, David J.

    2016-04-01

    In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea via studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.

  5. SEMANTIC INTEGRATION FOR AUTOMATIC ONTOLOGY MAPPING

    Directory of Open Access Journals (Sweden)

    Siham AMROUCH

    2013-11-01

    Full Text Available In the last decade, ontologies have played a key technology role for information sharing and agents interoperability in different application domains. In semantic web domain, ontologies are efficiently used to face the great challenge of representing the semantics of data, in order to bring the actual web to its full power and hence, achieve its objective. However, using ontologies as common and shared vocabularies requires a certain degree of interoperability between them. To confront this requirement, mapping ontologies is a solution that is not to be avoided. In deed, ontology mapping build a meta layer that allows different applications and information systems to access and share their informations, of course, after resolving the different forms of syntactic, semantic and lexical mismatches. In the contribution presented in this paper, we have integrated the semantic aspect based on an external lexical resource, wordNet, to design a new algorithm for fully automatic ontology mapping. This fully automatic character features the main difference of our contribution with regards to the most of the existing semi-automatic algorithms of ontology mapping, such as Chimaera, Prompt, Onion, Glue, etc. To better enhance the performances of our algorithm, the mapping discovery stage is based on the combination of two sub-modules. The former analysis the concept’s names and the later analysis their properties. Each one of these two sub-modules is it self based on the combination of lexical and semantic similarity measures.

  6. Ontological semantics in modified categorial grammar

    DEFF Research Database (Denmark)

    Szymczak, Bartlomiej Antoni

    2009-01-01

    Categorial Grammar is a well established tool for describing natural language semantics. In the current paper we discuss some of its drawbacks and how it could be extended to overcome them. We use the extended version for deriving ontological semantics from text. A proof-of-concept implementation...

  7. Semantic repository and ontology mapping

    NARCIS (Netherlands)

    Gracia, J.; Trna, M.; Lozano, E.; Nguyen, T.T.; Gómez-Pérez, A.; Montaña, C.; Liem, J.

    2010-01-01

    This document discusses the core Semantic Technologies in DynaLearn: i) The semantic repository, which supports the online storage and access of qualitative reasoning models, ii) the grounding process, which establishes semantic equivalences between the concepts in the models and the concepts in a

  8. Construct Primary Education Semantic Ontology Library Based Mind Mapping

    Directory of Open Access Journals (Sweden)

    Hu Dong-Hong

    2016-01-01

    Full Text Available Researches conducted for Mind mapping application in primary education semantic ontology, while considering unique characteristics of primary education, found there were rare widely used ontology libraries and few connections between ontology libraries for information sharing and reuse. In addition, primary semantic ontology library lack precise definitions of the semantics. This paper proposed a solution based on cluster structure derived from mind mapping by providing logical description of the ontologies to precisely define semantics; Meanwhile, tags were adapted to associate different ontologies to form ontology library.

  9. Semantator: Annotating Clinical Narratives with Semantic Web Ontologies

    OpenAIRE

    Song, Dezhao; Chute, Christopher G; Tao, Cui

    2012-01-01

    To facilitate clinical research, clinical data needs to be stored in a machine processable and understandable way. Manual annotating clinical data is time consuming. Automatic approaches (e.g., Natural Language Processing systems) have been adopted to convert such data into structured formats; however, the quality of such automatically extracted data may not always be satisfying. In this paper, we propose Semantator, a semi-automatic tool for document annotation with Semantic Web ontologies. ...

  10. Bridge Ontology:A Multi-Ontologies-Based Approach for Semantic Annotation

    Institute of Scientific and Technical Information of China (English)

    WANG Peng; XU Bao-wen; LU Jian-jiang; LI Yan-hui; JIANG Jian-hua

    2004-01-01

    Representing the relationships between ontologies is the key problem of semantic annotations based on multi-ontologies.Traditional approaches only had the ability of denoting the simple concept subsumption relations between ontologies.Through analyzing and classifying the relationships between ontologies, the idea of bridge ontology was proposed, which had the powerful capability of expressing the complex relationships between concepts and relationships between relations in multi-ontologies.Meanwhile, a new approach employing bridge ontology was proposed to deal with the multi-ontologies-based semantic annotation problem.The bridge ontology is a peculiar ontology, which can be created and maintained conveniently, and is effective in the multi-ontologies-based semantic annotation.The approach using bridge ontology has the advantages of low-cost, scalable, robust in the web circumstance, and avoiding the unnecessary ontology extending and integration.

  11. The Development Process of the Semantic Web and Web Ontology

    Directory of Open Access Journals (Sweden)

    K.Vanitha

    2011-08-01

    Full Text Available This paper deals with the semantic web and web ontology. The existing ontology development processes are not catered towards casual web ontology development, a notion analogous to standard web page development. Ontologies have become common on the World-Wide Web[2]. Key features of this process include easy and rapid creation of ontological skeletons, searching and linking to existing ontologies and a natural language-based technique to improve presentation of ontologies[6]. Ontologies, however, vary greatly in size, scope and semantics. They can range from generic upper-level ontologies to domain-specific schemas. The success of the Semantic Web is based on the existance of numerous distributed ontologies, using which users can annotate their data, thereby enabling shared machine readable content. This paper elaborates the stages in a casual ontology development process.

  12. Computing an Ontological Semantics for a Natural Language Fragment

    DEFF Research Database (Denmark)

    Szymczak, Bartlomiej Antoni

    The key objective of the research that has been carried out has been to establish theoretically sound connections between the following two areas: • Computational processing of texts in natural language by means of logical methods • Theories and methods for engineering of formal ontologies We have...... tried to establish a domain independent “ontological semantics” for relevant fragments of natural language. The purpose of this research is to develop methods and systems for taking advantage of formal ontologies for the purpose of extracting the meaning contents of texts. This functionality...... is desirable e.g. for future content–based search systems in contrast to today’s keyword based search systems (viz., Google) which rely chiefly on recognition of stated keywords in the targeted text. Logical methods were introduced into semantic theories for natural language already during the 60’s in what...

  13. Model Mapping Approach Based on Ontology Semantics

    Directory of Open Access Journals (Sweden)

    Jinkui Hou

    2013-09-01

    Full Text Available The mapping relations between different models are the foundation for model transformation in model-driven software development. On the basis of ontology semantics, model mappings between different levels are classified by using structural semantics of modeling languages. The general definition process for mapping relations is explored, and the principles of structure mapping are proposed subsequently. The approach is further illustrated by the mapping relations from class model of object oriented modeling language to the C programming codes. The application research shows that the approach provides a theoretical guidance for the realization of model mapping, and thus can make an effective support to model-driven software development

  14. Semantic Query Optimisation with Ontology Simulation

    CERN Document Server

    Gupta, Siddharth

    2010-01-01

    Semantic Web is, without a doubt, gaining momentum in both industry and academia. The word "Semantic" refers to "meaning" - a semantic web is a web of meaning. In this fast changing and result oriented practical world, gone are the days where an individual had to struggle for finding information on the Internet where knowledge management was the major issue. The semantic web has a vision of linking, integrating and analysing data from various data sources and forming a new information stream, hence a web of databases connected with each other and machines interacting with other machines to yield results which are user oriented and accurate. With the emergence of Semantic Web framework the na\\"ive approach of searching information on the syntactic web is clich\\'e. This paper proposes an optimised semantic searching of keywords exemplified by simulation an ontology of Indian universities with a proposed algorithm which ramifies the effective semantic retrieval of information which is easy to access and time sav...

  15. SEMANTIC TERM BASED INFORMATION RETRIEVAL USING ONTOLOGY

    OpenAIRE

    2014-01-01

    Information Searching and retrieval is a challenging task in the traditional keyword based textual information retrieval system. In the growing information age, adding huge data every day the searching problem also augmented. Keyword based retrieval system returns bulk of junk document irrelevant to query. To address the limitations, this paper proposed query terms along with semantic terms for information retrieval using multiple ontology reference. User query sometimes reflects multiple ...

  16. Combining Ontology Development Methodologies and Semantic Web Platforms for E-government Domain Ontology Development

    CERN Document Server

    Dombeu, Jean Vincent Fonou; 10.5121/ijwest.2011.2202

    2011-01-01

    One of the key challenges in electronic government (e-government) is the development of systems that can be easily integrated and interoperated to provide seamless services delivery to citizens. In recent years, Semantic Web technologies based on ontology have emerged as promising solutions to the above engineering problems. However, current research practicing semantic development in e-government does not focus on the application of available methodologies and platforms for developing government domain ontologies. Furthermore, only a few of these researches provide detailed guidelines for developing semantic ontology models from a government service domain. This research presents a case study combining an ontology building methodology and two state-of-the-art Semantic Web platforms namely Protege and Java Jena ontology API for semantic ontology development in e-government. Firstly, a framework adopted from the Uschold and King ontology building methodology is employed to build a domain ontology describing th...

  17. EXPRESS: EXPressing REstful Semantic Services Using Domain Ontologies

    Science.gov (United States)

    Alowisheq, Areeb; Millard, David E.; Tiropanis, Thanassis

    Existing approaches to Semantic Web Services (SWS) require a domain ontology and a semantic description of the service. In the case of lightweight SWS approaches, such as SAWSDL, service description is achieved by semantically annotating existing web service interfaces. Other approaches such as OWL-S and WSMO describe services in a separate ontology. So, existing approaches separate service description from domain description, therefore increasing design efforts. We propose EXPRESS a lightweight approach to SWS that requires the domain ontology definition only. Its simplicity stems from the similarities between REST and the Semantic Web such as resource realization, self describing representations, and uniform interfaces. The semantics of a service is elicited from a resource's semantic description in the domain ontology and the semantics of the uniform interface, hence eliminating the need for ontologically describing services. We provide an example that illustrates EXPRESS and then discuss how it compares to SA-REST and WSMO.

  18. Semantic-Driven e-Government: Application of Uschold and King Ontology Building Methodology for Semantic Ontology Models Development

    CERN Document Server

    Fonou-Dombeu, Jean Vincent; 10.5121/ijwest.2011.2401

    2011-01-01

    Electronic government (e-government) has been one of the most active areas of ontology development during the past six years. In e-government, ontologies are being used to describe and specify e-government services (e-services) because they enable easy composition, matching, mapping and merging of various e-government services. More importantly, they also facilitate the semantic integration and interoperability of e-government services. However, it is still unclear in the current literature how an existing ontology building methodology can be applied to develop semantic ontology models in a government service domain. In this paper the Uschold and King ontology building methodology is applied to develop semantic ontology models in a government service domain. Firstly, the Uschold and King methodology is presented, discussed and applied to build a government domain ontology. Secondly, the domain ontology is evaluated for semantic consistency using its semi-formal representation in Description Logic. Thirdly, an...

  19. Ontology and Formal Semantics - Integration Overdue

    CERN Document Server

    Saba, Walid S

    2007-01-01

    In this note we suggest that difficulties encountered in natural language semantics are, for the most part, due to the use of mere symbol manipulation systems that are devoid of any content. In such systems, where there is hardly any link with our common-sense view of the world, and it is quite difficult to envision how one can formally account for the considerable amount of content that is often implicit, but almost never explicitly stated in our everyday discourse. The solution, in our opinion, is a compositional semantics grounded in an ontology that reflects our commonsense view of the world and the way we talk about it in ordinary language. In the compositional logic we envision there are ontological (or first-intension) concepts, and logical (or second-intension) concepts, and where the ontological concepts include not only Davidsonian events, but other abstract objects as well (e.g., states, processes, properties, activities, attributes, etc.) It will be demonstrated here that in such a framework, a nu...

  20. Semantic Query Optimisation with Ontology Simulation

    Directory of Open Access Journals (Sweden)

    Siddharth Gupta

    2010-11-01

    Full Text Available Semantic Web is, without a doubt, gaining momentum in both industry and academia. The word“Semantic” refers to “meaning” – a semantic web is a web of meaning. In this fast changing and resultoriented practical world, gone are the days where an individual had to struggle for finding informationon the Internet where knowledge management was the major issue. The semantic web has a vision oflinking, integrating and analysing data from various data sources and forming a new information stream,hence a web of databases connected with each other and machines interacting with other machines toyield results which are user oriented and accurate. With the emergence of Semantic Web framework thenaïve approach of searching information on the syntactic web is cliché. This paper proposes an optimisedsemantic searching of keywords exemplified by simulation an ontology of Indian universities with aproposed algorithm which ramifies the effective semantic retrieval of information which is easy to accessand time saving.

  1. Understanding Semantic Web and Ontologies: Theory and Applications

    CERN Document Server

    Taye, Mohammad Mustafa

    2010-01-01

    Semantic Web is actually an extension of the current one in that it represents information more meaningfully for humans and computers alike. It enables the description of contents and services in machine-readable form, and enables annotating, discovering, publishing, advertising and composing services to be automated. It was developed based on Ontology, which is considered as the backbone of the Semantic Web. In other words, the current Web is transformed from being machine-readable to machine-understandable. In fact, Ontology is a key technique with which to annotate semantics and provide a common, comprehensible foundation for resources on the Semantic Web. Moreover, Ontology can provide a common vocabulary, a grammar for publishing data, and can supply a semantic description of data which can be used to preserve the Ontologies and keep them ready for inference. This paper provides basic concepts of web services and the Semantic Web, defines the structure and the main applications of ontology, and provides ...

  2. Handbook of metadata, semantics and ontologies

    CERN Document Server

    Sicilia, Miguel-Angel

    2013-01-01

    Metadata research has emerged as a discipline cross-cutting many domains, focused on the provision of distributed descriptions (often called annotations) to Web resources or applications. Such associated descriptions are supposed to serve as a foundation for advanced services in many application areas, including search and location, personalization, federation of repositories and automated delivery of information. Indeed, the Semantic Web is in itself a concrete technological framework for ontology-based metadata. For example, Web-based social networking requires metadata describing people and

  3. Semantic Content Filtering with Wikipedia and Ontologies

    CERN Document Server

    Malo, Pekka; Ahlgren, Oskar; Wallenius, Jyrki; Korhonen, Pekka

    2010-01-01

    The use of domain knowledge is generally found to improve query efficiency in content filtering applications. In particular, tangible benefits have been achieved when using knowledge-based approaches within more specialized fields, such as medical free texts or legal documents. However, the problem is that sources of domain knowledge are time-consuming to build and equally costly to maintain. As a potential remedy, recent studies on Wikipedia suggest that this large body of socially constructed knowledge can be effectively harnessed to provide not only facts but also accurate information about semantic concept-similarities. This paper describes a framework for document filtering, where Wikipedia's concept-relatedness information is combined with a domain ontology to produce semantic content classifiers. The approach is evaluated using Reuters RCV1 corpus and TREC-11 filtering task definitions. In a comparative study, the approach shows robust performance and appears to outperform content classifiers based on ...

  4. Enabling Ontology Based Semantic Queries in Biomedical Database Systems.

    Science.gov (United States)

    Zheng, Shuai; Wang, Fusheng; Lu, James

    2014-03-01

    There is a lack of tools to ease the integration and ontology based semantic queries in biomedical databases, which are often annotated with ontology concepts. We aim to provide a middle layer between ontology repositories and semantically annotated databases to support semantic queries directly in the databases with expressive standard database query languages. We have developed a semantic query engine that provides semantic reasoning and query processing, and translates the queries into ontology repository operations on NCBO BioPortal. Semantic operators are implemented in the database as user defined functions extended to the database engine, thus semantic queries can be directly specified in standard database query languages such as SQL and XQuery. The system provides caching management to boosts query performance. The system is highly adaptable to support different ontologies through easy customizations. We have implemented the system DBOntoLink as an open source software, which supports major ontologies hosted at BioPortal. DBOntoLink supports a set of common ontology based semantic operations and have them fully integrated with a database management system IBM DB2. The system has been deployed and evaluated with an existing biomedical database for managing and querying image annotations and markups (AIM). Our performance study demonstrates the high expressiveness of semantic queries and the high efficiency of the queries.

  5. Ontology Based Resolution of Semantic Conflicts in Information Integration

    Institute of Scientific and Technical Information of China (English)

    LU Han; LI Qing-zhong

    2004-01-01

    Semantic conflict is the conflict caused by using different ways in heterogeneous systems to express the same entity in reality.This prevents information integration from accomplishing semantic coherence.Since ontology helps to solve semantic problems, this area has become a hot topic in information integration.In this paper, we introduce semantic conflict into information integration of heterogeneous applications.We discuss the origins and categories of the conflict, and present an ontology-based schema mapping approach to eliminate semantic conflicts.

  6. CODEX: exploration of semantic changes between ontology versions.

    Science.gov (United States)

    Hartung, Michael; Gross, Anika; Rahm, Erhard

    2012-03-15

    Life science ontologies substantially change over time to meet the requirements of their users and to include the newest domain knowledge. Thus, an important task is to know what has been modified between two versions of an ontology (diff). This diff should contain all performed changes as compact and understandable as possible. We present CODEX (Complex Ontology Diff Explorer), a tool that allows determining semantic changes between two versions of an ontology, which users can interactively analyze in multiple ways.

  7. Product line based ontology development for semantic web service

    DEFF Research Database (Denmark)

    Zhang, Weishan; Kunz, Thomas

    2006-01-01

    and evolution. In this paper, we present a product line based reuseoriented ontology development methodology which integrates ontology development with design by reuse and design for reuse. The basic building block in our approach is the meta-ontology. In the first stage, reengineering of existing ontologies...... will lead to the initial implementation of the meta-onotologies using design by reuse and with the objective of design for reuse. After that step new ontologies could be generated by reusing these meta-ontologies. We demonstrate our approach with a Semantic Web Service application to show how to build...

  8. Ontology alignment architecture for semantic sensor Web integration.

    Science.gov (United States)

    Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

    2013-09-18

    Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  9. Ontology Alignment Architecture for Semantic Sensor Web Integration

    Directory of Open Access Journals (Sweden)

    Bernardo Alarcos

    2013-09-01

    Full Text Available Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity. Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity’s names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  10. Ontology-based geographic information semantic metadata integration

    Science.gov (United States)

    Zhan, Qin; Li, Deren; Zhang, Xia; Xia, Yu

    2009-10-01

    Metadata is important to facilitate data sharing among Geospatial Information Communities in distributed environment. For unanimous understanding and standard production of metadata annotations, metadata specifications are documented such as Geographic Information Metadata Standard (ISO19115-2003), the Content Standard for Digital Geospatial Metadata (CSDGM), and so on. Though these specifications provide frameworks for description of geographic data, there are two problems which embarrass sufficiently data sharing. One problem is that specifications are lack of domainspecific semantics. Another problem is that specifications can not always solve semantic heterogeneities. To solve the former problem, an ontology-based geographic information metadata extension framework is proposed which can incorporate domain-specific semantics. Besides, for solving the later problem, metadata integration mechanism based on the proposed extension is studied. In this paper, integration of metadata is realized through integration of ontologies. So integration of ontologies is also discussed. By ontology-based geographic information semantic metadata integration, sharing of geographic data is realized more efficiently.

  11. Ontology Based Information Retrieval in Semantic Web: A Survey

    Directory of Open Access Journals (Sweden)

    Vishal Jain

    2013-09-01

    Full Text Available In present age of computers, there are various resources for gathering information related to given query like Radio Stations, Television, Internet and many more. Among them, Internet is considered as major factor for obtaining any information about a given domain. When a user wants to find some information, he/she enters a query and results are produced via hyperlinks linked to various documents available on web. But the information that is retrieved to us may or may not be relevant. This irrelevance is caused due to huge collection of documents available on web. Traditional search engines are based on keyword based searching that is unable to transform raw data into knowledgeable representation data. It is a cumbersome task to extract relevant information from large collection of web documents. These shortcomings have led to the concept of Semantic Web (SW and Ontology into existence. Semantic Web (SW is a well defined portal that helps in extracting relevant information using many Information Retrieval (IR techniques. Current Information Retrieval (IR techniques are not so advanced that they can be able to exploit semantic knowledge within documents and give precise result. The terms, Information Retrieval (IR, Semantic Web (SW and Ontology are used differently but they are interconnected with each other. Information Retrieval (IR technology and Web based Indexing contributes to existence of Semantic Web. Use of Ontology also contributes in building new generation of web- Semantic Web. With the help of ontologies, we can make content of web as it will be markup with the help of Semantic Web documents (SWD’s. Ontology is considered as backbone of Software system. It improves understanding between concepts used in Semantic Web (SW. So, there is need to build an ontology that uses well defined methodology and process of developing ontology is called Ontology Development.

  12. Algorithm to Match Ontologies on the Semantic Web

    Directory of Open Access Journals (Sweden)

    Alaa Qassim Al-Namiy

    2013-04-01

    Full Text Available It has been recognized that semantic data and knowledge extraction will significantly improve the capability of natural language interfaces to the semantic search engine. Semantic Web technology offers a vast scale of sharing and integration of distributed data sources by combining information easily. This will enable the user to find the information easily and efficiently. In this paper, we will explore some issues of developing algorithms for the Semantic Web. The first one to build the semantic contextual meaning by scanning the text, extract knowledge and automatically infer the meaning of the information from text that contains the search words in any sentence and correlate with hierarchical classes defined in the Ontology as a result of input resources. The second to discover the hierarchical relationships among terms (i.e. discover the semantic relations across hierarchical classifications. The proposed algorithm will be relying on a number of resources including Ontology and WordNet.

  13. Semantic Search among Heterogeneous Biological Databases Based on Gene Ontology

    Institute of Scientific and Technical Information of China (English)

    Shun-Liang CAO; Lei QIN; Wei-Zhong HE; Yang ZHONG; Yang-Yong ZHU; Yi-Xue LI

    2004-01-01

    Semantic search is a key issue in integration of heterogeneous biological databases. In thispaper, we present a methodology for implementing semantic search in BioDW, an integrated biological datawarehouse. Two tables are presented: the DB2GO table to correlate Gene Ontology (GO) annotated entriesfrom BioDW data sources with GO, and the semantic similarity table to record similarity scores derived fromany pair of GO terms. Based on the two tables, multifarious ways for semantic search are provided and thecorresponding entries in heterogeneous biological databases in semantic terms can be expediently searched.

  14. A Semantic Medical Multimedia Retrieval Approach Using Ontology Information Hiding

    OpenAIRE

    2013-01-01

    Searching useful information from unstructured medical multimedia data has been a difficult problem in information retrieval. This paper reports an effective semantic medical multimedia retrieval approach which can reflect the users’ query intent. Firstly, semantic annotations will be given to the multimedia documents in the medical multimedia database. Secondly, the ontology that represented semantic information will be hidden in the head of the multimedia documents. The main innovations of ...

  15. Syntactic-semantic treebank for domain ontology creation

    Directory of Open Access Journals (Sweden)

    Petya Osenova

    2015-11-01

    Full Text Available Syntactic-semantic treebank for domain ontology creation This paper focuses on the creation of a domain treebank for the purposes of compiling a domain ontology. The domain treebank is viewed as a suitable resource for extracting of semantic relations from syntactic structures. First, the steps for ontology building are considered. Then, the processing over glossaries and standards is described with regard to their syntactic annotation. The utility of deriving semantic knowledge from the Treebank is also illustrated via the basic phrases. The idea is that the domain knowledge is represented in the domain data, but via treebanking more linguistic patterns can be extracted, which to be mapped to concepts and relations in a domain ontology.

  16. Collaborative Semantic Annotation of Images : Ontology-Based Model

    Directory of Open Access Journals (Sweden)

    Damien E. ZOMAHOUN

    2015-12-01

    Full Text Available In the quest for models that could help to represen t the meaning of images, some approaches have used contextual knowledge by building semantic hierarchi es. Others have resorted to the integration of imag es analysis improvement knowledge and images interpret ation using ontologies. The images are often annotated with a set of keywords (or ontologies, w hose relevance remains highly subjective and relate d to only one interpretation (one annotator. However , an image can get many associated semantics because annotators can interpret it differently. Th e purpose of this paper is to propose a collaborati ve annotation system that brings out the meaning of im ages from the different interpretations of annotato rs. The different works carried out in this paper lead to a semantic model of an image, i.e. the different means that a picture may have. This method relies o n the different tools of the Semantic Web, especial ly ontologies.

  17. An Ontology Based Methodology for Satellite Data Semantic Interoperability

    Directory of Open Access Journals (Sweden)

    ABBURU, S.

    2015-08-01

    Full Text Available Satellites and ocean based observing system consists of various sensors and configurations. These observing systems transmit data in heterogeneous file formats and heterogeneous vocabulary from various data centers. These data centers maintain a centralized data management system that disseminates the observations to various research communities. Currently, different data naming conventions are being used by existing observing systems, thus leading to semantic heterogeneity. In this work, sensor data interoperability and semantics of the data are being addressed through ontologies. The present work provides an effective technical solution to address semantic heterogeneity through semantic technologies. These technologies provide interoperability, capability to build knowledge base, and framework for semantic information retrieval by developing an effective concept vocabulary through domain ontologies. The paper aims at a new methodology to interlink the multidisciplinary and heterogeneous sensor data products. A four phase methodology has been implemented to address satellite data semantic interoperability. The paper concludes with the evaluation of the methodology by linking and interfacing multiple ontologies to arrive at ontology vocabulary for sensor observations. Data from Indian Meteorological satellite INSAT-3D satellite have been used as a typical example to illustrate the concepts. This work on similar lines can also be extended to other sensor observations.

  18. A semantic medical multimedia retrieval approach using ontology information hiding.

    Science.gov (United States)

    Guo, Kehua; Zhang, Shigeng

    2013-01-01

    Searching useful information from unstructured medical multimedia data has been a difficult problem in information retrieval. This paper reports an effective semantic medical multimedia retrieval approach which can reflect the users' query intent. Firstly, semantic annotations will be given to the multimedia documents in the medical multimedia database. Secondly, the ontology that represented semantic information will be hidden in the head of the multimedia documents. The main innovations of this approach are cross-type retrieval support and semantic information preservation. Experimental results indicate a good precision and efficiency of our approach for medical multimedia retrieval in comparison with some traditional approaches.

  19. Geospatial semantics: beyond ontologies, towards an enactive approach

    CERN Document Server

    Di Donato, Pasquale

    2009-01-01

    Current approaches to semantics in the geospatial domain are mainly based on ontologies, but ontologies, since continue to build entirely on the symbolic methodology, suffers from the classical problems, e.g. the symbol grounding problem, affecting representational theories. We claim for an enactive approach to semantics, where meaning is considered to be an emergent feature arising context-dependently in action. Since representational theories are unable to deal with context, a new formalism is required toward a contextual theory of concepts. SCOP is considered a promising formalism in this sense and is briefly described.

  20. Ontology modularization to improve semantic medical image annotation.

    Science.gov (United States)

    Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

    2011-02-01

    Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results.

  1. Semantic web and the concept of global geo-ontology

    OpenAIRE

    Čeh, Marjan; Smole, Domen; Podobnikar, Tomaž

    2013-01-01

    Geographic information systems have been applied on the World Wide Web with different approaches and there is a need to recognize how different groups of users conceptualize the domain of geographic space. In our research, we present an attempt to model a semantic reference system in a semantic web by the concept of global geo-ontology. Taxonomy is based on general knowledge representation as physical and conceptual shapes, simultaneously with basic and advanced hum...

  2. Semantics, ontologies and eScience for the geosciences

    OpenAIRE

    Reitsma, Femke; Laxton, John; Ballard, Stuart; Kuhn, Werner; Abdelmoty, Alia

    2009-01-01

    Semantics, ontologies and eScience are key areas of research that aim to deal with the growing volume, number of sources and heterogeneity of geoscience data, information and knowledge. Following a workshop held at the eScience Institute in Edinburgh on the 7–9th of March 2008, this paper discusses some of the significant research topics and challenges for enhancing geospatial computing using semantic and grid technologies.

  3. Semantics, ontologies and eScience for the geosciences

    Science.gov (United States)

    Reitsma, Femke; Laxton, John; Ballard, Stuart; Kuhn, Werner; Abdelmoty, Alia

    2009-04-01

    Semantics, ontologies and eScience are key areas of research that aim to deal with the growing volume, number of sources and heterogeneity of geoscience data, information and knowledge. Following a workshop held at the eScience Institute in Edinburgh on the 7-9th of March 2008, this paper discusses some of the significant research topics and challenges for enhancing geospatial computing using semantic and grid technologies.

  4. ONTOLOGY BASED SEMANTIC KNOWLEDGE REPRESENTATION FOR SOFTWARE RISK MANAGEMENT

    Directory of Open Access Journals (Sweden)

    C.R.Rene Robin

    2010-10-01

    Full Text Available Domain specific knowledge representation is achieved through the use of ontologies. The ontology model of software risk management is an effective approach for the intercommunion between people from teaching and learning community, the communication and interoperation among various knowledge oriented applications, and the share and reuse of the software. But the lack of formal representation tools for domain modeling results in taking liberties with conceptualization. This paper narrates an ontology based semantic knowledge representation mechanism and the architecture we proposed has been successfully implemented for the domain software riskmanagement.

  5. Semantic Web Based Efficient Search Using Ontology and Mathematical Model

    Directory of Open Access Journals (Sweden)

    K.Palaniammal

    2014-01-01

    Full Text Available The semantic web is the forthcoming technology in the world of search engine. It becomes mainly focused towards the search which is more meaningful rather than the syntactic search prevailing now. This proposed work concerns about the semantic search with respect to the educational domain. In this paper, we propose semantic web based efficient search using ontology and mathematical model that takes into account the misleading, unmatched kind of service information, lack of relevant domain knowledge and the wrong service queries. To solve these issues in this framework is designed to make three major contributions, which are ontology knowledge base, Natural Language Processing (NLP techniques and search model. Ontology knowledge base is to store domain specific service ontologies and service description entity (SDE metadata. The search model is to retrieve SDE metadata as efficient for Education lenders, which include mathematical model. The Natural language processing techniques for spell-check and synonym based search. The results are retrieved and stored in an ontology, which in terms prevents the data redundancy. The results are more accurate to search, sensitive to spell check and synonymous context. This paper reduces the user’s time and complexity in finding for the correct results of his/her search text and our model provides more accurate results. A series of experiments are conducted in order to respectively evaluate the mechanism and the employed mathematical model.

  6. An Upper Ontology for E-Learning Material Semantic Annotations

    Directory of Open Access Journals (Sweden)

    T. Khdour

    2013-12-01

    Full Text Available Recent research reveals a great interest to introduce the Semantic Web as a promising technology for realizing eLearning requirements. The new, dynamic and distributed business world has motivated the research on developing eLearning. ELearning is efficient, task relevant and just-in-time learning. It gives the learner the ability to efficiently access the related educational resources just-in-time from any place. The vision of the Semantic Web is to make the Web data not only processable but also understandable so it can be used by machines not just for display purposes but for automation, integration and reuse of data across various applications. This study investigates the role of Semantic Web in realizing the e-learning requirements. It proposes an ontology-based e-learning framework that considers the main three component roles of the e-learning architecture: an author, a learner and a repository. The study also shed the light on improving the conventional metadata standards that are used to describe learning materials by proposing a semantic-based ontology to describe three different dimensions of the learning material: content, context and structure. Adopting the proposed ontology would result in facilitating both the process of finding suitable learning materials to build up a certain course and the process of navigating through the learning course.

  7. Educational Advertising Ontology: A Domain-Dependent Ontology for Semantic Advertising Networks

    Directory of Open Access Journals (Sweden)

    Lilac A.E. Al-Safadi

    2010-01-01

    Full Text Available Problem statement: Currently advertising networks connects Web site owners (Publishers that want to host advertisements with advertisers who want to run advertisements. Advertising networks' reliance on only the keywords in the content without an accurate interpretation of the context of the page, results in displaying irrelevant and unappealing ads on the web page. Approach: Ontologies provided a shared and common understanding of a domain that can be communicated between people and across application systems. Our objective was to create a domain-dependent Ontology to play a major role in supporting information exchange processes in semantic advertising networks. Results: Results for the prototype of matching ads with publishers had been presented in terms of precision and recall. High precision was shown and analysis of results was given in detail. Conclusion: The proposed Ontology is effective for advertising networks at a semantic level.

  8. CNTRO 2.0: A Harmonized Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives

    OpenAIRE

    Tao, Cui; Solbrig, Harold R; Chute, Christopher G

    2011-01-01

    The Clinical Narrative Temporal Relation Ontology (CNTRO) has been developed for the purpose of allowing temporal information of clinical data to be semantically annotated and queried, and using inference to expose new temporal features and relations based on the semantic assertions and definitions of the temporal aspects in the ontology. While CNTRO provides a formal semantic foundation to leverage the semantic-web techniques, it is still necessary to arrive at a shared set of semantics and ...

  9. A method exploiting syntactic patterns and the UMLS semantics for aligning biomedical ontologies: the case of OBO disease ontologies.

    Science.gov (United States)

    Marquet, Gwenaëlle; Mosser, Jean; Burgun, Anita

    2007-12-01

    The OBO ontologies include more than 50 standard vocabularies that cover different domains, including genomics, chemistry, anatomy and phenotype. Ontology alignment is a means to build consistent biomedical ontologies compatible with standard vocabularies and dedicated to specific domains, such as cancer. An alignment is defined as a set of pairs of concepts, coming from two ontologies, related by a relation R, R not being restricted to the equivalence or subsumption relations. Alignment is performed in three major steps: first, the concepts that are equivalent in the ontologies are identified; second the pairs of concepts that are related although not equivalent are searched for; third the relations between the concepts are characterized. We have developed a method to align ontologies that exploits the compositionality of the terms in OBO ontologies, uses the UMLS to provide synonyms and relations, and defines syntactico-semantic patterns that characterize semantically the relations between concepts. We have applied it to four OBO phenotype ontologies: mouse pathology, human disease, mammalian phenotype, and PATO. We found 386 pairs of equivalent concepts and 20,461 pairs of concepts where one concept name is included in the other term. Among the 20,460 inclusions, we were able to provide a semantic categorization for 2682 relations. In 2552 cases, the relation was present and semantically defined in the UMLS Metathesaurus, in 131 cases the relation was characterized through semantic patterns. Our approach may help to find the semantic relations between concepts in ontologies.

  10. Using ontologies to improve semantic interoperability in health data.

    Science.gov (United States)

    Liyanage, Harshana; Krause, Paul; De Lusignan, Simon

    2015-07-10

    The present-day health data ecosystem comprises a wide array of complex heterogeneous data sources. A wide range of clinical, health care, social and other clinically relevant information are stored in these data sources. These data exist either as structured data or as free-text. These data are generally individual person-based records, but social care data are generally case based and less formal data sources may be shared by groups. The structured data may be organised in a proprietary way or be coded using one-of-many coding, classification or terminologies that have often evolved in isolation and designed to meet the needs of the context that they have been developed. This has resulted in a wide range of semantic interoperability issues that make the integration of data held on these different systems changing. We present semantic interoperability challenges and describe a classification of these. We propose a four-step process and a toolkit for those wishing to work more ontologically, progressing from the identification and specification of concepts to validating a final ontology. The four steps are: (1) the identification and specification of data sources; (2) the conceptualisation of semantic meaning; (3) defining to what extent routine data can be used as a measure of the process or outcome of care required in a particular study or audit and (4) the formalisation and validation of the final ontology. The toolkit is an extension of a previous schema created to formalise the development of ontologies related to chronic disease management. The extensions are focused on facilitating rapid building of ontologies for time-critical research studies.

  11. Using ontologies to improve semantic interoperability in health data

    Directory of Open Access Journals (Sweden)

    Harshana Liyanage

    2015-07-01

    Full Text Available The present–day health data ecosystem comprises a wide array of complex heterogeneous data sources. A wide range of clinical, health care, social and other clinically relevant information are stored in these data sources. These data exist either as structured data or as free-text. These data are generally individual personbased records, but social care data are generally case based and less formal data sources may be shared by groups. The structured data may be organised in a proprietary way or be coded using one-of-many coding, classification or terminologies that have often evolved in isolation and designed to meet the needs of the context that they have been developed. This has resulted in a wide range of semantic interoperability issues that make the integration of data held on these different systems changing. We present semantic interoperability challenges and describe a classification of these. We propose a four-step process and a toolkit for those wishing to work more ontologically, progressing from the identification and specification of concepts to validating a final ontology. The four steps are: (1 the identification and specification of data sources; (2 the conceptualisation of semantic meaning; (3 defining to what extent routine data can be used as a measure of the process or outcome of care required in a particular study or audit and (4 the formalisation and validation of the final ontology. The toolkit is an extension of a previous schema created to formalise the development of ontologies related to chronic disease management. The extensions are focused on facilitating rapid building of ontologies for time-critical research studies. 

  12. Ontology-Driven Semantic Search for Brazilian Portuguese Clinical Notes.

    Science.gov (United States)

    Hasan, Sadid A; Zhu, Xianshu; Liu, Joey; Barra, Claudia M; Oliveira, Lucas; Farri, Oladimeji

    2015-01-01

    The emerging penetration of Health IT in Latin America (especially in Brazil) has exacerbated the ever-increasing amount of Electronic Health Record (EHR) clinical free text documents.This imposes a workflow efficiency challenge on clinicians who need to synthesize such documents during the typically time-constrained patient care. We propose an ontology-driven semantic search framework that effectively supports clinicians' information synthesis at the point of care.

  13. Automatic Tamil lyric generation based on ontological interpretation for semantics

    Indian Academy of Sciences (India)

    Rajeswari Sridhar; D Jalin Gladis; Kameswaran Ganga; G Dhivya Prabha

    2014-02-01

    This system proposes an -gram based approach to automatic Tamil lyric generation, by the ontological semantic interpretation of the input scene. The approach is based on identifying the semantics conveyed in the scenario, thereby making the system understand the situation and generate lyrics accordingly. The heart of the system includes the ontological interpretation of the scenario, and the selection of the appropriate tri-grams for generating the lyrics. To fulfill this, we have designed a new ontology with weighted edges, where the edges correspond to a set of sentences, which indicate a relationship, and are represented as a tri-gram. Once the appropriate tri-grams are selected, the root words from these tri-grams are sent to the morphological generator, to form words in their packed form. These words are then assembled to form the final lyrics. Parameters of poetry like rhyme, alliteration, simile, vocative words, etc., are also taken care of by the system. Using this approach, we achieved an average accuracy of 77.3% with respect to the exact semantic details being conveyed in the generated lyrics.

  14. Semantic description of liver CT images: an ontological approach.

    Science.gov (United States)

    Kokciyan, Nadin; Turkay, Rustu; Uskudarli, Suzan; Yolum, Pinar; Bakir, Baris; Acar, Burak

    2014-07-01

    Radiologists inspect CT scans and record their observations in reports to communicate with physicians. These reports may suffer from ambiguous language and inconsistencies resulting from subjective reporting styles, which present challenges in interpretation. Standardization efforts, such as the lexicon RadLex for radiology terms, aim to address this issue by developing standard vocabularies. While such vocabularies handle consistent annotation, they fall short in sufficiently processing reports for intelligent applications. To support such applications, the semantics of the concepts as well as their relationships must be modeled, for which, ontologies are effective. They enable the software to make inferences beyond what is present in the reports. This paper presents the open-source ontology onlira (Ontology of the Liver for Radiology), which is developed to support such intelligent applications, such as identifying and ranking similar liver patient cases. onlira is introduced in terms of its concepts, properties, and relations. Examples of real liver patient cases are provided for illustration purposes. The ontology is evaluated in terms of its ability to express real liver patient cases and address semantic queries.

  15. Semantic description and recognition of patterns

    Institute of Scientific and Technical Information of China (English)

    杨立; 戴汝为

    1996-01-01

    An algebraic semantic approach for the description and recognition of patterns is presented.Specifically,patterns are assumed as algebraic structures,and semantic constraints are given in the form of equational specifications.By such an idea,to recogniz a pattern is to check the validity of an equational conjecture by term rewriting.Such an approach is demonstrated through examples.

  16. A measure of semantic similarity between gene ontology terms based on semantic pathway covering

    Institute of Scientific and Technical Information of China (English)

    LI Rong; CAO Shunliang; LI Yuanyuan; TAN Hao; ZHU Yangyong; ZHONG Yang; LI Yixue

    2006-01-01

    Semantic similarity between Gene Ontology (GO) terms is critical in resolving semantic heterogeneousness when integrating heterogeneous biological databases. Traditionally, distance based and information content based measures are two major methods.In this paper, a new method based on semantic pathway covering is proposed and an algorithm, COMBINE algorithm, is presented,which considers information contents of two given nodes and those of all nodes included in the two nodes' pathways. Experiments show that COMBINE algorithm obtains the highest correlation index compared with those distance based and information content based algorithms.

  17. Towards Ontology-driven Discourse: From Semantic Graphs to Multimedia Presentations

    NARCIS (Netherlands)

    Geurts, J.P.T.M.; Bocconi, S.; Ossenbruggen, J.R. van; Hardman, L.

    2003-01-01

    Traditionally, research in applying Semantic Web technology to multimedia information systems has focused on using annotations and ontologies to improve the retrieval process. This paper concentrates on improving the presentation of the retrieval results. First, our approach uses ontological domain

  18. Towards ontology-driven discourse: from semantic graphs to multimedia presentations

    NARCIS (Netherlands)

    Geurts, J.P.T.M.; Bocconi, S.; Ossenbruggen, J.R. van; Hardman, L.

    2003-01-01

    Traditionally, research in applying Semantic Web technology to multimedia information systems has focused on using annotations and ontologies to improve the retrieval process. This paper concentrates on improving the presentation of the retrieval results. First, our approach uses ontological domain

  19. Semantic Information Retrieval Using Ontology in University Domain

    Directory of Open Access Journals (Sweden)

    Swathi Rajasurya

    2012-11-01

    Full Text Available Today’s conventional search engines hardly do provide the essential content relevant to the user’s searchquery. This is because the context and semantics of the request made by the user is not analyzed to the fullextent. So here the need for a semantic web search arises. SWS is upcoming in the area of web searchwhich combines Natural Language Processing and Artificial Intelligence. The objective of the work donehere is to design, develop and implement a semantic search engine- SIEU(Semantic InformationExtraction in University Domain confined to the university domain. SIEU uses ontology as a knowledgebase for the information retrieval process. It is not just a mere keyword search. It is one layer above whatGoogle or any other search engines retrieve by analyzing just the keywords. Here the query is analyzedboth syntactically and semantically. The developed system retrieves the web results more relevant to theuser query through keyword expansion. The results obtained here will be accurate enough to satisfy therequest made by the user. The level of accuracy will be enhanced since the query is analyzed semantically.The system will be of great use to the developers and researchers who work on web. The Google results arere-ranked and optimized for providing the relevant links. For ranking an algorithm has been applied whichfetches more apt results for the user query

  20. Ontologies: Semantic Nirvana for Earth Science Model Interoperability? (Invited)

    Science.gov (United States)

    Graybeal, J.

    2009-12-01

    The Challenge: When we build a given model, we do so to meet today's needs. If the model is good, new people will want to use it in new ways. That tests how well the model can work in new contexts: new user groups, new science domains, or new data providers or data users. We can say a model is interoperable if it works well in each new case, with few or no changes. Here we deal with perhaps the least-addressed part of model interoperability: semantic interoperability, the ability of models to understand the meaning of each other's data. The Scenario: A model has been built that uses observational data, and creates output data sets. In subsequent years, the model must (a) be connected to another model and exchange data with it; (b) be evaluated and used by a scientist in another domain; (c) document its outputs for two different repositories that use different keywords; and (d) identify and incorporate new observation streams as they come on-line. All these steps are mostly done manually today, and explanations about the data exchanged in similar form. Can we make them more efficient, or even automated, by leveraging good semantic practices? A problem in each case is the use of local or community naming conventions that are not known to all parties. How can this be improved? The Reality: Many models use the standard name conventions and vocabularies specified by the netCDF COARDS Climate and Forecast conventions. These provide a good basic level of 'semantic interoperability', and for this reason alone Earth science models are semantically far ahead of most other Earth science data systems. Yet these conventions aren't always used, aren't always sufficient, and don't help us interoperate with lots of existing systems. What are the issues for semantic interoperability in modeling, how do ontologies and other semantic capabilities help us fix them, and are ontologies worth the trouble?

  1. Automatic Learning of Ontologies for the Semantic Web: experiment lexical learning

    OpenAIRE

    2012-01-01

    This paper proposes the design of a System for Automatic Learning of Ontologies and Lexical Information (SALOX) for the Dynamic Semantic Ontological Framework for the Semantic Web (DSOFSW). DSOFSW interprets query in natural language (Spanish) to the web, and is composed by five parts; a linguistic ontology for the grammar of Spanish, a lexicon for the lexical information, a database of facts about the system experiences, a task ontology for the linguistic analysis process, and an interpretat...

  2. Semantic Feature Based Arabic Opinion Mining Using Ontology

    Directory of Open Access Journals (Sweden)

    Abdullah M. Alkadri

    2016-05-01

    Full Text Available with the increase of opinionated reviews on the web, automatically analyzing and extracting knowledge from those reviews is very important. However, it is a challenging task to be done manually. Opinion mining is a text mining discipline that automatically performs such a task. Most researches done in this field were focused on English texts with very limited researches on Arabic language. This scarcity is because there are a lot of obstacles in Arabic. The aim of this paper is to develop a novel semantic feature-based opinion mining framework for Arabic reviews. This framework utilizes the semantic of ontologies and lexicons in the identification of opinion features and their polarity. Experiments showed that the proposed framework achieved a good level of performance compared with manually collected test data.

  3. Ontology-Based Semantic Annotation for Problem Set Archives in the Web

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Aimming at the difficulty in getting semantic information from each problem in problem set archives, We propose a new method of ontology-based semantic annotation for problem set archives, which utilizes programming knowledge domain ontology to add semantic annotations to problems in the Web. The system we developed adds semantic annotation for each problem in the form of Extensible Makeup Language. Our method overcomes the difficulty of extracting semantics from problem set archives and the efficiency of this method is demonstrated through a case study. Having semantic annotations of problems, a student can efficiently locate the problems that logically correspond to his knowledge.

  4. OM2R : semantic documentation of ontology mapping lifecycle to support retrieval and reuse of ontology mappings

    OpenAIRE

    2014-01-01

    Ontology mappings are of critical importance for the Linked Data and the Semantic Web communities as they can help to mitigate the effects of heterogeneities, which are a major obstacle to the promise of interoperability of knowledge. To reduce creation costs and enable automated runtime integration, the description, discovery and most of all re-use of existing ontology mappings are needed. Meta-data can help to retrieve ontology mappings, to apply them and to m...

  5. ILexicOn: toward an ECD-compliant interlingual lexical ontology described with semantic web formalisms

    CERN Document Server

    Lefrançois, Maxime

    2012-01-01

    We are interested in bridging the world of natural language and the world of the semantic web in particular to support natural multilingual access to the web of data. In this paper we introduce a new type of lexical ontology called interlingual lexical ontology (ILexicOn), which uses semantic web formalisms to make each interlingual lexical unit class (ILUc) support the projection of its semantic decomposition on itself. After a short overview of existing lexical ontologies, we briefly introduce the semantic web formalisms we use. We then present the three layered architecture of our approach: i) the interlingual lexical meta-ontology (ILexiMOn); ii) the ILexicOn where ILUcs are formally defined; iii) the data layer. We illustrate our approach with a standalone ILexicOn, and introduce and explain a concise human-readable notation to represent ILexicOns. Finally, we show how semantic web formalisms enable the projection of a semantic decomposition on the decomposed ILUc.

  6. Integrating Semantic Features for Enhancing Arabic Named Entity Recognition

    Directory of Open Access Journals (Sweden)

    Hamzah A. Alsayadi

    2016-03-01

    Full Text Available Named Entity Recognition (NER is currently an essential research area that supports many tasks in NLP. Its goal is to find a solution to boost accurately the named entities identification. This paper presents an integrated semantic-based Machine learning (ML model for Arabic Named Entity Recognition (ANER problem. The basic idea of that model is to combine several linguistic features and to utilize syntactic dependencies to infer semantic relations between named entities. The proposed model focused on recognizing three types of named entities: person, organization and location. Accordingly, it combines internal features that represented linguistic features as well as external features that represent the semantic of relations between the three named entities to enhance the accuracy of recognizing them using external knowledge source such as Arabic WordNet ontology (ANW. We introduced both features to CRF classifier, which are effective for ANER. Experimental results show that this approach can achieve an overall F-measure around 87.86% and 84.72% for ANERCorp and ALTEC datasets respectively.

  7. Toward semantic interoperability with linked foundational ontologies in ROMULUS

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-06-01

    Full Text Available A purpose of a foundational ontology is to solve interoperability issues among ontologies. Many foundational ontologies have been developed, reintroducing the ontology interoperability problem. We address this with the new online foundational...

  8. ONTOLOGY BASED MEANINGFUL SEARCH USING SEMANTIC WEB AND NATURAL LANGUAGE PROCESSING TECHNIQUES

    Directory of Open Access Journals (Sweden)

    K. Palaniammal

    2013-10-01

    Full Text Available The semantic web extends the current World Wide Web by adding facilities for the machine understood description of meaning. The ontology based search model is used to enhance efficiency and accuracy of information retrieval. Ontology is the core technology for the semantic web and this mechanism for representing formal and shared domain descriptions. In this paper, we proposed ontology based meaningful search using semantic web and Natural Language Processing (NLP techniques in the educational domain. First we build the educational ontology then we present the semantic search system. The search model consisting three parts which are embedding spell-check, finding synonyms using WordNet API and querying ontology using SPARQL language. The results are both sensitive to spell check and synonymous context. This paper provides more accurate results and the complete details for the selected field in a single page.

  9. Automatic Learning of Ontologies for the Semantic Web: experiment lexical learning

    Directory of Open Access Journals (Sweden)

    Eduard Puerto

    2012-07-01

    Full Text Available This paper proposes the design of a System for Automatic Learning of Ontologies and Lexical Information (SALOX for the Dynamic Semantic Ontological Framework for the Semantic Web (DSOFSW. DSOFSW interprets query in natural language (Spanish to the web, and is composed by five parts; a linguistic ontology for the grammar of Spanish, a lexicon for the lexical information, a database of facts about the system experiences, a task ontology for the linguistic analysis process, and an interpretative ontology of the context. SALOX integrates several methods, approaches and techniques for information extraction, discovery and actualization (pragmatic (user profile, context knowledge, lexical and semantic linguistic information, etc. in order to update the knowledge used for DSOFSW. SALOX has a component to map the sources of learning with the learning methods, and another to update the linguistic ontology and the lexicon of the DSOFSW. Specifically, in this paper we present the design of the learning unit of lexical information.

  10. Semantic Ontology Method of Learning Resource based on the Approximate Subgraph Isomorphism

    Directory of Open Access Journals (Sweden)

    Lili Zhang

    2014-02-01

    Full Text Available Digital learning resource ontology is often based on different specification building. It is hard to find resources by linguistic ontology matching method. The existing structural matching method fails to solve the problem of calculation of structural similarity well. For the heterogeneity problem among learning resource ontology, an algorithm is presented based on subgraph approximate isomorphism. First of all, we can preprocess the resource of clustering algorithm through the semantic analysis, then describe the ontology by the directed graph and calculate the similarity, and finally judge the semantic relations through calculating and analyzing different resource between the ontology of different learning resource to achieve semantic compatibility or mapping of ontology. This method is an extension of existing methods in ontology matching. Under the comprehensive application of features such as edit distance and hierarchical relations, the similarity of graph structures between two ontologies is calculated. And, the ontology matching is determined on the condition of subgraph approximate isomorphism based on the alternately mapping of nodes and arcs in the describing graphs of ontologies. An example is used to demonstrate this ontology matching process and the time complexity is analyzed to explain its effectiveness

  11. CNTRO: A Semantic Web Ontology for Temporal Relation Inferencing in Clinical Narratives.

    Science.gov (United States)

    Tao, Cui; Wei, Wei-Qi; Solbrig, Harold R; Savova, Guergana; Chute, Christopher G

    2010-11-13

    Using Semantic-Web specifications to represent temporal information in clinical narratives is an important step for temporal reasoning and answering time-oriented queries. Existing temporal models are either not compatible with the powerful reasoning tools developed for the Semantic Web, or designed only for structured clinical data and therefore are not ready to be applied on natural-language-based clinical narrative reports directly. We have developed a Semantic-Web ontology which is called Clinical Narrative Temporal Relation ontology. Using this ontology, temporal information in clinical narratives can be represented as RDF (Resource Description Framework) triples. More temporal information and relations can then be inferred by Semantic-Web based reasoning tools. Experimental results show that this ontology can represent temporal information in real clinical narratives successfully.

  12. Towards Ontology-driven Discourse: From Semantic Graphs to Multimedia Presentations

    NARCIS (Netherlands)

    J.P.T.M. Geurts (Joost); S. Bocconi; J.R. van Ossenbruggen (Jacco); L. Hardman (Lynda)

    2003-01-01

    textabstractTraditionally, research in applying Semantic Web technology to multimedia information systems has focused on using annotations and ontologies to improve the retrieval process. This paper concentrates on improving the presentation of the retrieval results. First, our approach uses

  13. Towards ontology-driven discourse: from semantic graphs to multimedia presentations

    NARCIS (Netherlands)

    J.P.T.M. Geurts (Joost); S. Bocconi; J.R. van Ossenbruggen (Jacco); L. Hardman (Lynda)

    2003-01-01

    textabstractTraditionally, research in applying Semantic Web technology to multimedia information systems has focused on using annotations and ontologies to improve the retrieval process. This paper concentrates on improving the presentation of the retrieval results. First, our approach uses

  14. The use of web ontology languages and other semantic web tools in drug discovery.

    Science.gov (United States)

    Chen, Huajun; Xie, Guotong

    2010-05-01

    To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

  15. Hybrid ontology for semantic information retrieval model using keyword matching indexing system.

    Science.gov (United States)

    Uthayan, K R; Mala, G S Anandha

    2015-01-01

    Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.

  16. Hybrid Ontology for Semantic Information Retrieval Model Using Keyword Matching Indexing System

    Directory of Open Access Journals (Sweden)

    K. R. Uthayan

    2015-01-01

    Full Text Available Ontology is the process of growth and elucidation of concepts of an information domain being common for a group of users. Establishing ontology into information retrieval is a normal method to develop searching effects of relevant information users require. Keywords matching process with historical or information domain is significant in recent calculations for assisting the best match for specific input queries. This research presents a better querying mechanism for information retrieval which integrates the ontology queries with keyword search. The ontology-based query is changed into a primary order to predicate logic uncertainty which is used for routing the query to the appropriate servers. Matching algorithms characterize warm area of researches in computer science and artificial intelligence. In text matching, it is more dependable to study semantics model and query for conditions of semantic matching. This research develops the semantic matching results between input queries and information in ontology field. The contributed algorithm is a hybrid method that is based on matching extracted instances from the queries and information field. The queries and information domain is focused on semantic matching, to discover the best match and to progress the executive process. In conclusion, the hybrid ontology in semantic web is sufficient to retrieve the documents when compared to standard ontology.

  17. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Science.gov (United States)

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  18. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Directory of Open Access Journals (Sweden)

    Ramona L Walls

    Full Text Available The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques, as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1 individual organisms, including voucher specimens from ecological studies and museum specimens, 2 bulk or environmental samples (e.g., gut contents, soil, water that include DNA, other molecules, and potentially many organisms, especially microbes, and 3 survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and

  19. ELE: An Ontology-Based System Integrating Semantic Search and E-Learning Technologies

    Science.gov (United States)

    Barbagallo, A.; Formica, A.

    2017-01-01

    ELSE (E-Learning for the Semantic ECM) is an ontology-based system which integrates semantic search methodologies and e-learning technologies. It has been developed within a project of the CME (Continuing Medical Education) program--ECM (Educazione Continua nella Medicina) for Italian participants. ELSE allows the creation of e-learning courses…

  20. The Semantic Mapping of Archival Metadata to the CIDOC CRM Ontology

    Science.gov (United States)

    Bountouri, Lina; Gergatsoulis, Manolis

    2011-01-01

    In this article we analyze the main semantics of archival description, expressed through Encoded Archival Description (EAD). Our main target is to map the semantics of EAD to the CIDOC Conceptual Reference Model (CIDOC CRM) ontology as part of a wider integration architecture of cultural heritage metadata. Through this analysis, it is concluded…

  1. Fish Ontology framework for taxonomy-based fish recognition

    Science.gov (United States)

    Ali, Najib M.; Khan, Haris A.; Then, Amy Y-Hui; Ving Ching, Chong; Gaur, Manas

    2017-01-01

    Life science ontologies play an important role in Semantic Web. Given the diversity in fish species and the associated wealth of information, it is imperative to develop an ontology capable of linking and integrating this information in an automated fashion. As such, we introduce the Fish Ontology (FO), an automated classification architecture of existing fish taxa which provides taxonomic information on unknown fish based on metadata restrictions. It is designed to support knowledge discovery, provide semantic annotation of fish and fisheries resources, data integration, and information retrieval. Automated classification for unknown specimens is a unique feature that currently does not appear to exist in other known ontologies. Examples of automated classification for major groups of fish are demonstrated, showing the inferred information by introducing several restrictions at the species or specimen level. The current version of FO has 1,830 classes, includes widely used fisheries terminology, and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish species globally, the FO will be an indispensable tool for fish scientists and other interested users. PMID:28929028

  2. Research on Data Integration of the Semantic Web Based on Ontology Learning Technology

    Directory of Open Access Journals (Sweden)

    Ruiling Zhang

    2013-07-01

    Full Text Available Goal of ontology learning is to use machine learning and statistical techniques, by means of automatic or semi-automatic, and obtain the expected from the existing data resources. Web data integration based on ontology is web data mapping information in the source to the process of ontology concepts. The goal of semantic Web is to provide a computer for semantic Internet information can be understood, thus the computer to identify the information, and the automatic interpretation, exchange and processing. The paper presents the research on data integration of the semantic web based on ontology learning technology. Theory and experiments show that compared with the method of concept lattice construction algorithm has certain superiority.

  3. Domain XML semantic integration based on extraction rules and ontology mapping

    Directory of Open Access Journals (Sweden)

    Huayu LI

    2016-08-01

    Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

  4. Ontology modeling of semantics in social media:Public issue knowledge base (PIKB)of the Weibo

    Institute of Scientific and Technical Information of China (English)

    Yan; ZHOU; Wei; LI; Xingfu; YUAN; Pengyi; ZHANG

    2014-01-01

    Purpose:This study aims to construct an ontology to model the semantics of social media streams,in particular,trending topics and public issues.Design/methodology/approach:Our knowledge base included 10 public events and topics from Weibo respectively,which were collected through keyword search and a crawler program.We used a semi-automatic approach to model and annotate the semantics in social media,and adapted the multi-layered ontology to refine the design based on previous researches,then we used named entity recognition(NER) to extract entities to instantiate the ontology.Relationships were extracted based on co-occurrence measures.Finally,we manually conducted post-filtering evaluation and edited the extracted entities and relationships.Findings:An initial assessment demonstrated that our multi-layered ontology supports various types of queries and analyses in the public issue knowledge base(PIKB),which can serve as an effective tool to query,understand and trace public issues.Research limitations:Manual involvement cannot meet the requirements for challenges of sustainable developments.Since the relationships extracted are fully based on the co-occurrence of entities,rich semantic relationships,such as how much the key players have been involved,could not be fully reflected.Besides,the user evaluation is necessary for further ontology assessment.Practical implications:The PIKB can be used by regular Web users and policy makers to query,understand,and make sense of public events and topics.The methodology and reusable ontology model are useful for institutions that are interested in making use of the social media data.Originality/value:In this study,a multi-layered ontology is applied to model the evolving semantics of public events and trending topics in social media,and the semi-automatic approach could make it possible to extract entities and relationships from large amount of unstructured short texts of user generated content(UGC) from social media.

  5. Scalable Medical Image Understanding by Fusing Cross-Modal Object Recognition with Formal Domain Semantics

    Science.gov (United States)

    Möller, Manuel; Sintek, Michael; Buitelaar, Paul; Mukherjee, Saikat; Zhou, Xiang Sean; Freund, Jörg

    Recent advances in medical imaging technology have dramatically increased the amount of clinical image data. In contrast, techniques for efficiently exploiting the rich semantic information in medical images have evolved much slower. Despite the research outcomes in image understanding, current image databases are still indexed by manually assigned subjective keywords instead of the semantics of the images. Indeed, most current content-based image search applications index image features that do not generalize well and use inflexible queries. This slow progress is due to the lack of scalable and generic information representation systems which can abstract over the high dimensional nature of medical images as well as semantically model the results of object recognition techniques. We propose a system combining medical imaging information with ontological formalized semantic knowledge that provides a basis for building universal knowledge repositories and gives clinicians fully cross-lingual and cross-modal access to biomedical information.

  6. Enabling semantic similarity estimation across multiple ontologies: an evaluation in the biomedical domain.

    Science.gov (United States)

    Sánchez, David; Solé-Ribalta, Albert; Batet, Montserrat; Serratosa, Francesc

    2012-02-01

    The estimation of the semantic similarity between terms provides a valuable tool to enable the understanding of textual resources. Many semantic similarity computation paradigms have been proposed both as general-purpose solutions or framed in concrete fields such as biomedicine. In particular, ontology-based approaches have been very successful due to their efficiency, scalability, lack of constraints and thanks to the availability of large and consensus ontologies (like WordNet or those in the UMLS). These measures, however, are hampered by the fact that only one ontology is exploited and, hence, their recall depends on the ontological detail and coverage. In recent years, some authors have extended some of the existing methodologies to support multiple ontologies. The problem of integrating heterogeneous knowledge sources is tackled by means of simple terminological matchings between ontological concepts. In this paper, we aim to improve these methods by analysing the similarity between the modelled taxonomical knowledge and the structure of different ontologies. As a result, we are able to better discover the commonalities between different ontologies and hence, improve the accuracy of the similarity estimation. Two methods are proposed to tackle this task. They have been evaluated and compared with related works by means of several widely-used benchmarks of biomedical terms using two standard ontologies (WordNet and MeSH). Results show that our methods correlate better, compared to related works, with the similarity assessments provided by experts in biomedicine.

  7. Bi-directional semantic similarity for gene ontology to optimize biological and clinical analyses.

    Science.gov (United States)

    Bien, Sang Jay; Park, Chan Hee; Shim, Hae Jin; Yang, Woongcheol; Kim, Jihun; Kim, Ju Han

    2012-01-01

    Semantic similarity analysis facilitates automated semantic explanations of biological and clinical data annotated by biomedical ontologies. Gene ontology (GO) has become one of the most important biomedical ontologies with a set of controlled vocabularies, providing rich semantic annotations for genes and molecular phenotypes for diseases. Current methods for measuring GO semantic similarities are limited to considering only the ancestor terms while neglecting the descendants. One can find many GO term pairs whose ancestors are identical but whose descendants are very different and vice versa. Moreover, the lower parts of GO trees are full of terms with more specific semantics. This study proposed a method of measuring semantic similarities between GO terms using the entire GO tree structure, including both the upper (ancestral) and the lower (descendant) parts. Comprehensive comparison studies were performed with well-known information content-based and graph structure-based semantic similarity measures with protein sequence similarities, gene expression-profile correlations, protein-protein interactions, and biological pathway analyses. The proposed bidirectional measure of semantic similarity outperformed other graph-based and information content-based methods.

  8. A relation based measure of semantic similarity for Gene Ontology annotations

    Directory of Open Access Journals (Sweden)

    Gaudin Benoit

    2008-11-01

    Full Text Available Abstract Background Various measures of semantic similarity of terms in bio-ontologies such as the Gene Ontology (GO have been used to compare gene products. Such measures of similarity have been used to annotate uncharacterized gene products and group gene products into functional groups. There are various ways to measure semantic similarity, either using the topological structure of the ontology, the instances (gene products associated with terms or a mixture of both. We focus on an instance level definition of semantic similarity while using the information contained in the ontology, both in the graphical structure of the ontology and the semantics of relations between terms, to provide constraints on our instance level description. Semantic similarity of terms is extended to annotations by various approaches, either though aggregation operations such as min, max and average or through an extrapolative method. These approaches introduce assumptions about how semantic similarity of terms relates to the semantic similarity of annotations that do not necessarily reflect how terms relate to each other. Results We exploit the semantics of relations in the GO to construct an algorithm called SSA that provides the basis of a framework that naturally extends instance based methods of semantic similarity of terms, such as Resnik's measure, to describing annotations and not just terms. Our measure attempts to correctly interpret how terms combine via their relationships in the ontological hierarchy. SSA uses these relationships to identify the most specific common ancestors between terms. We outline the set of cases in which terms can combine and associate partial order constraints with each case that order the specificity of terms. These cases form the basis for the SSA algorithm. The set of associated constraints also provide a set of principles that any improvement on our method should seek to satisfy. Conclusion We derive a measure of semantic

  9. Developing an University Ontology in Education Domain using Protégé for Semantic Web

    Directory of Open Access Journals (Sweden)

    SANJAY KUMAR MALIK,

    2010-09-01

    Full Text Available The current web is based on HTML which is not able to be exploited by information retrieval techniques and hence processing of information on web is mostly restricted to manual keyword searches which results in irrelevant information retrieval . This limitation may be overcome by a new web architecture known as semantic web which is an intelligent and meaningful web proposed by Sir Tim Berner’s Lee. In his roadmap for semantic web, Ontology plays a pivotal role in information exchange, use and re-use knowledge, shared and common understanding of a domain that can be communicated between people and across application systems which is the goal of semantic web. Ontology is used to capture knowledge about any domain of interest with the objective of incorporating the machineunderstandable data on the current human-readable web. Web Ontology Language (OWL is a semantic markup language for sharing ontologies on the web and is designed for use by software agents to empower them to comprehend the meaning of web documents. Ontology is a broad term including a wide range of activities,complexities and issues in which Ontology Development is one of the most fundamental and significant concern. There may be various methodologies or tools for ontology development . In this paper, we consider the education domain and demonstrate thedevelopment of an University Ontology using Protégé 3.4 Editor. Indraprastha University, Delhi, India has been taken as an example for the Ontology Development and various aspects like super class and sub class hierarchy, creating a sub class, instances for classes illustr

  10. An Ontology-Based Approach for Semantic Conflict Resolution in Database Integration

    Institute of Scientific and Technical Information of China (English)

    Qiang Liu; Tao Huang; Shao-Hua Liu; Hua Zhong

    2007-01-01

    An important task in database integration is to resolve data conflicts, on both schema-level and semantic-level.Especially difficult the latter is. Some existing ontology-based approaches have been criticized for their lack of domain generality and semantic richness. With the aim to overcome these limitations, this paper introduces a systematic approach for detecting and resolving various semantic conflicts in heterogeneous databases, which includes two important parts: a semantic conflict representation model based on our classification framework of semantic conflicts, and a methodology for detecting and resolving semantic conflicts based on this model. The system has been developed, experimental evaluations on which indicate that this approach can resolve much of the semantic conflicts effectively, and keep independent of domains and integration patterns.

  11. Building an Event Ontology for Historical Domain to Support Semantic Document Retrieval

    Directory of Open Access Journals (Sweden)

    Fatihah Ramli

    2016-12-01

    Full Text Available In the past years, there has been increasing concern on ontology for its ability to explain data semantics in the usual manner independent of the data source characteristics, providing a schema that allows interchanging data between heterogeneous information systems and users. The ontology development in some areas is not expected due to a large amount of information, particularly in history, leading its semantic impossible. Several works have been designed to improve the technological aspects of ontology, such as the representation of language and inference mechanisms, and less attention has been paid to practical results development of application methods. This paper presents a discussion on the experience and processes during ontology building in history: historical documents retrieval based on the event.

  12. Evaluation of Multistrategy Classifiers for Heterogeneous Ontology Matching On the Semantic Web

    Institute of Scientific and Technical Information of China (English)

    PAN Le-yun; LIU Xiao-qiang; MA Fan-yuan

    2005-01-01

    On the semantic web, data interoperability and ontology heterogeneity are becoming ever more important issues. To resolve these problems, multiple classification methods can be used to learn the matching between ontologies. The paper uses the general statistic classification method to discover category features in data instances and use the first-order learning algorithm FOIL to exploit the semantic relations among data instances. When using mulfistrategy learning approach, a central problem is the evaluation of multistrategy classifiers. The goal and the conditions of using multistrategy classifiers within ontology matching are different from the ones for general text classification. This paper describes the combination rule of multiple classifiers called the Best Outstanding Champion, which is suitable for heterogeneous ontology mapping. On the prediction results of individual methods, the method can well accumulate the correct matching of alone classifier. The experiments show that the approach achieves high accuracy on real-world domain.

  13. Developing a semantically rich ontology for the biobank-administration domain.

    Science.gov (United States)

    Brochhausen, Mathias; Fransson, Martin N; Kanaskar, Nitin V; Eriksson, Mikael; Merino-Martinez, Roxana; Hall, Roger A; Norlin, Loreana; Kjellqvist, Sanela; Hortlund, Maria; Topaloglu, Umit; Hogan, William R; Litton, Jan-Eric

    2013-10-08

    Biobanks are a critical resource for translational science. Recently, semantic web technologies such as ontologies have been found useful in retrieving research data from biobanks. However, recent research has also shown that there is a lack of data about the administrative aspects of biobanks. These data would be helpful to answer research-relevant questions such as what is the scope of specimens collected in a biobank, what is the curation status of the specimens, and what is the contact information for curators of biobanks. Our use cases include giving researchers the ability to retrieve key administrative data (e.g. contact information, contact's affiliation, etc.) about the biobanks where specific specimens of interest are stored. Thus, our goal is to provide an ontology that represents the administrative entities in biobanking and their relations. We base our ontology development on a set of 53 data attributes called MIABIS, which were in part the result of semantic integration efforts of the European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). The previous work on MIABIS provided the domain analysis for our ontology. We report on a test of our ontology against competency questions that we derived from the initial BBMRI use cases. Future work includes additional ontology development to answer additional competency questions from these use cases. We created an open-source ontology of biobank administration called Ontologized MIABIS (OMIABIS) coded in OWL 2.0 and developed according to the principles of the OBO Foundry. It re-uses pre-existing ontologies when possible in cooperation with developers of other ontologies in related domains, such as the Ontology of Biomedical Investigation. OMIABIS provides a formalized representation of biobanks and their administration. Using the ontology and a set of Description Logic queries derived from the competency questions that we identified, we were able to retrieve test data with perfect

  14. A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

    Science.gov (United States)

    El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

    2015-11-01

    Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. Ontology Language to Support Description of Experiment Control System Semantics, Collaborative Knowledge-Base Design and Ontology Reuse

    Energy Technology Data Exchange (ETDEWEB)

    Vardan Gyurjyan, D Abbott, G Heyes, E Jastrzembski, B Moffit, C Timmer, E Wolin

    2009-10-01

    In this paper we discuss the control domain specific ontology that is built on top of the domain-neutral Resource Definition Framework (RDF). Specifically, we will discuss the relevant set of ontology concepts along with the relationships among them in order to describe experiment control components and generic event-based state machines. Control Oriented Ontology Language (COOL) is a meta-data modeling language that provides generic means for representation of physics experiment control processes and components, and their relationships, rules and axioms. It provides a semantic reference frame that is useful for automating the communication of information for configuration, deployment and operation. COOL has been successfully used to develop a complete and dynamic knowledge-base for experiment control systems, developed using the AFECS framework.

  16. Gene-based and semantic structure of the Gene Ontology as a complex network

    Science.gov (United States)

    Coronnello, Claudia; Tumminello, Michele; Miccichè, Salvatore

    2016-09-01

    The last decade has seen the advent and consolidation of ontology based tools for the identification and biological interpretation of classes of genes, such as the Gene Ontology. The Gene Ontology (GO) is constantly evolving over time. The information accumulated time-by-time and included in the GO is encoded in the definition of terms and in the setting up of semantic relations amongst terms. Here we investigate the Gene Ontology from a complex network perspective. We consider the semantic network of terms naturally associated with the semantic relationships provided by the Gene Ontology consortium. Moreover, the GO is a natural example of bipartite network of terms and genes. Here we are interested in studying the properties of the projected network of terms, i.e. a gene-based weighted network of GO terms, in which a link between any two terms is set if at least one gene is annotated in both terms. One aim of the present paper is to compare the structural properties of the semantic and the gene-based network. The relative importance of terms is very similar in the two networks, but the community structure changes. We show that in some cases GO terms that appear to be distinct from a semantic point of view are instead connected, and appear in the same community when considering their gene content. The identification of such gene-based communities of terms might therefore be the basis of a simple protocol aiming at improving the semantic structure of GO. Information about terms that share large gene content might also be important from a biomedical point of view, as it might reveal how genes over-expressed in a certain term also affect other biological processes, molecular functions and cellular components not directly linked according to GO semantics.

  17. The next generation of similarity measures that fully explore the semantics in biomedical ontologies.

    Science.gov (United States)

    Couto, Francisco M; Pinto, H Sofia

    2013-10-01

    There is a prominent trend to augment and improve the formality of biomedical ontologies. For example, this is shown by the current effort on adding description logic axioms, such as disjointness. One of the key ontology applications that can take advantage of this effort is the conceptual (functional) similarity measurement. The presence of description logic axioms in biomedical ontologies make the current structural or extensional approaches weaker and further away from providing sound semantics-based similarity measures. Although beneficial in small ontologies, the exploration of description logic axioms by semantics-based similarity measures is computational expensive. This limitation is critical for biomedical ontologies that normally contain thousands of concepts. Thus in the process of gaining their rightful place, biomedical functional similarity measures have to take the journey of finding how this rich and powerful knowledge can be fully explored while keeping feasible computational costs. This manuscript aims at promoting and guiding the development of compelling tools that deliver what the biomedical community will require in a near future: a next-generation of biomedical similarity measures that efficiently and fully explore the semantics present in biomedical ontologies.

  18. Ontology-based Semantic Search Engine for Healthcare Services

    Directory of Open Access Journals (Sweden)

    Jotsna Molly Rajan

    2012-04-01

    Full Text Available With the development of Web Services, the retrieval of relevant services has become a challenge. The keyword-based discovery mechanism using UDDI and WSDL is insufficient due to the retrievalof a large amount of irrelevant information. Also, keywords are insufficient in expressing semantic concepts since a single concept can be referred using syntactically different terms. Hence, service capabilities need to be manually analyzed, which lead to the development of the Semantic Web for automatic service discovery andretrieval of relevant services and resources. This work proposes the incorporation of Semantic matching methodology in Semantic Web for improving the efficiency and accuracy of the discovery mechanism.

  19. On Constructing, Grouping and Using Topical Ontology for Semantic Matching

    Science.gov (United States)

    Tang, Yan; de Baer, Peter; Zhao, Gang; Meersman, Robert

    An ontology topic is used to group concepts from different contexts (or even from different domain ontologies). This paper presents a pattern-driven modeling methodology for constructing and grouping topics in an ontology (PAD-ON methodology), which is used for matching similarities between competences in the human resource management (HRM) domain. The methodology is supported by a tool called PAD-ON. This paper demonstrates our recent achievement in the work from the EC Prolix project. The paper approach is applied to the training processes at British Telecom as the test bed.

  20. GeoSciGraph: An Ontological Framework for EarthCube Semantic Infrastructure

    Science.gov (United States)

    Gupta, A.; Schachne, A.; Condit, C.; Valentine, D.; Richard, S.; Zaslavsky, I.

    2015-12-01

    The CINERGI (Community Inventory of EarthCube Resources for Geosciences Interoperability) project compiles an inventory of a wide variety of earth science resources including documents, catalogs, vocabularies, data models, data services, process models, information repositories, domain-specific ontologies etc. developed by research groups and data practitioners. We have developed a multidisciplinary semantic framework called GeoSciGraph semantic ingration of earth science resources. An integrated ontology is constructed with Basic Formal Ontology (BFO) as its upper ontology and currently ingests multiple component ontologies including the SWEET ontology, GeoSciML's lithology ontology, Tematres controlled vocabulary server, GeoNames, GCMD vocabularies on equipment, platforms and institutions, software ontology, CUAHSI hydrology vocabulary, the environmental ontology (ENVO) and several more. These ontologies are connected through bridging axioms; GeoSciGraph identifies lexically close terms and creates equivalence class or subclass relationships between them after human verification. GeoSciGraph allows a community to create community-specific customizations of the integrated ontology. GeoSciGraph uses the Neo4J,a graph database that can hold several billion concepts and relationships. GeoSciGraph provides a number of REST services that can be called by other software modules like the CINERGI information augmentation pipeline. 1) Vocabulary services are used to find exact and approximate terms, term categories (community-provided clusters of terms e.g., measurement-related terms or environmental material related terms), synonyms, term definitions and annotations. 2) Lexical services are used for text parsing to find entities, which can then be included into the ontology by a domain expert. 3) Graph services provide the ability to perform traversal centric operations e.g., finding paths and neighborhoods which can be used to perform ontological operations like

  1. A Reusable and Interoperable Semantic Classification Tool which Integrates Owl Ontology

    Directory of Open Access Journals (Sweden)

    Saadia Lgarch

    2012-11-01

    Full Text Available In e-Learning systems, tutor plays a very important role to support learners, and guarantee a learning of quality. A successful collaboration between learners and their tutor requires the use of communication tools. Thanks to their flexibility in terms of time, the asynchronous tools as discussion forum are the most used. However this type of tools generates a great mass of messages making tutoring an operation complex to manage, hence the need of a classification tool of messages. We proposed in a first step a semantics classification tool, which is based on the LSA and thesaurus. The possibility that ontology provides to overcome the limitations of the thesaurus encouraged us to use it to control our vocabulary. By the way of our proposed selection algorithm, the OWL ontology is queried to generate new terms which are used to build the LSA matrix. The integration of formal OWL ontology provides a highly relevant semantic classification of messages, and the reuse by other applications of ontological knowledge base is also guaranteed. The interoperability and the knowledge exchange between systems are also ensured by ontology integrated. In order to ensure its reuse and interoperability with systems which requesting for its service of classification, the implementation of our semantic classifier tool basing on the SOA is adopted and it will be explained and tested in this work.

  2. An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework

    Science.gov (United States)

    Gao, Wenlong

    2012-01-01

    The ontology approach has been accepted as a very promising approach to semantic integration today. However, because of the diversity of focuses and its various connections to other research domains, the core concepts, theoretical and technical approaches, and research areas of this domain still remain unclear. Such ambiguity makes it difficult to…

  3. Correlating Information Contents of Gene Ontology Terms to Infer Semantic Similarity of Gene Products

    Directory of Open Access Journals (Sweden)

    Mingxin Gan

    2014-01-01

    Full Text Available Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson’s correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

  4. An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework

    Science.gov (United States)

    Gao, Wenlong

    2012-01-01

    The ontology approach has been accepted as a very promising approach to semantic integration today. However, because of the diversity of focuses and its various connections to other research domains, the core concepts, theoretical and technical approaches, and research areas of this domain still remain unclear. Such ambiguity makes it difficult to…

  5. Correlating information contents of gene ontology terms to infer semantic similarity of gene products.

    Science.gov (United States)

    Gan, Mingxin

    2014-01-01

    Successful applications of the gene ontology to the inference of functional relationships between gene products in recent years have raised the need for computational methods to automatically calculate semantic similarity between gene products based on semantic similarity of gene ontology terms. Nevertheless, existing methods, though having been widely used in a variety of applications, may significantly overestimate semantic similarity between genes that are actually not functionally related, thereby yielding misleading results in applications. To overcome this limitation, we propose to represent a gene product as a vector that is composed of information contents of gene ontology terms annotated for the gene product, and we suggest calculating similarity between two gene products as the relatedness of their corresponding vectors using three measures: Pearson's correlation coefficient, cosine similarity, and the Jaccard index. We focus on the biological process domain of the gene ontology and annotations of yeast proteins to study the effectiveness of the proposed measures. Results show that semantic similarity scores calculated using the proposed measures are more consistent with known biological knowledge than those derived using a list of existing methods, suggesting the effectiveness of our method in characterizing functional relationships between gene products.

  6. Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

    Directory of Open Access Journals (Sweden)

    Rong Gui

    2016-08-01

    Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

  7. An XPath-based OWL storage model for effective ontology management in Semantic Web environment

    Institute of Scientific and Technical Information of China (English)

    Jinhyung KIM; Dongwon JEONG; Doo-kwon BAIK

    2009-01-01

    With the rapid growth of the Web, the volume of information on the Web is increasing exponentially. However,information on the current Web is only understandable to humans, and this makes precise information retrieval difficult. To solve this problem, the Semantic Web was proposed. We must use ontology languages that can assign data the semantics for realizing the Semantic Web. One of the representative ontology languages is the Web ontology language OWL, adopted as a recommendation by the World-Wide Web Consortium (W3C). OWL includes hierarchical structural information between classes or properties. Therefore, an efficient OWL storage model that considers a hierarchical structure for effective information retrieval on the Semantic Web is required. In this paper we suggest an XPath-based OWL storage (XPOS) model, which includes hierarchical information between classes or properties in XPath form, and enables intuitive and effective information retrieval. Also, we show the comparative evaluation results for the performance of the XPOS model, Sesame, and the XML file system-based storage (XFSS) model, in terms of query processing and ontology updating.

  8. Using Domain Ontology in a Semantic Blogging System for Construction Professionals

    Institute of Scientific and Technical Information of China (English)

    Cynthia Changxin Wang; Dongbai Xue

    2008-01-01

    Smooth communication is essential for the success of construction projects. As an easy-to-use,context-rich, and high-capacity communication tool, blogging is gaining popularity in construction industry. In this paper, the features of biogging technology and how it could benefit construction organizations are pre-sented. To further improve the effectiveness of blogging technology in information and knowledge sharing,an ontology-based semantic blogging system is proposed. Semantic blogging is an extension of conven-tional blogging and ontology is the key enabling technology for it. Domain-ontology-based semantic blogging site is composed of a network of concepts, which are cleady defined and interlinked according to their con-text and bound to certain behaviors. This paper reports how the e-Cognos ontology was implemented into a blogging system and how the system functions to process its contents. The paper concludes that using on-tology-based semantic blogging site can greatly enhance information sharing between construction profes-sionals and it is a very promising tool for construction communities to publish and share their experience.

  9. Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

    Science.gov (United States)

    Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E

    2014-01-01

    The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.

  10. Semantic particularity measure for functional characterization of gene sets using gene ontology.

    Science.gov (United States)

    Bettembourg, Charles; Diot, Christian; Dameron, Olivier

    2014-01-01

    Genetic and genomic data analyses are outputting large sets of genes. Functional comparison of these gene sets is a key part of the analysis, as it identifies their shared functions, and the functions that distinguish each set. The Gene Ontology (GO) initiative provides a unified reference for analyzing the genes molecular functions, biological processes and cellular components. Numerous semantic similarity measures have been developed to systematically quantify the weight of the GO terms shared by two genes. We studied how gene set comparisons can be improved by considering gene set particularity in addition to gene set similarity. We propose a new approach to compute gene set particularities based on the information conveyed by GO terms. A GO term informativeness can be computed using either its information content based on the term frequency in a corpus, or a function of the term's distance to the root. We defined the semantic particularity of a set of GO terms Sg1 compared to another set of GO terms Sg2. We combined our particularity measure with a similarity measure to compare gene sets. We demonstrated that the combination of semantic similarity and semantic particularity measures was able to identify genes with particular functions from among similar genes. This differentiation was not recognized using only a semantic similarity measure. Semantic particularity should be used in conjunction with semantic similarity to perform functional analysis of GO-annotated gene sets. The principle is generalizable to other ontologies.

  11. A Semantic-based Clustering Method to Build Domain Ontology from Multiple Heterogeneous Knowledge Sources

    Institute of Scientific and Technical Information of China (English)

    LING Ling; HU Yu-jin; WANG Xue-lin; LI Cheng-gang

    2006-01-01

    In order to improve the efficiency of ontology construction from heterogeneous knowledge sources, a semantic-based approach is presented. The ontology will be constructed with the application of cluster technique in an incremental way.Firstly, terms will be extracted from knowledge sources and congregate a term set after pretreat-ment. Then the concept set will be built via semantic-based clustering according to semanteme of terms provided by WordNet. Next, a concept tree is constructed in terms of mapping rules between semanteme relationships and concept relationships. The semi-automatic approach can avoid non-consistence due to knowledge engineers having different understanding of the same concept and the obtained ontology is easily to be expanded.

  12. The Semantic Retrieval of Spatial Data Service Based on Ontology in SIG

    Science.gov (United States)

    Sun, S.; Liu, D.; Li, G.; Yu, W.

    2011-08-01

    The research of SIG (Spatial Information Grid) mainly solves the problem of how to connect different computing resources, so that users can use all the resources in the Grid transparently and seamlessly. In SIG, spatial data service is described in some kinds of specifications, which use different meta-information of each kind of services. This kind of standardization cannot resolve the problem of semantic heterogeneity, which may limit user to obtain the required resources. This paper tries to solve two kinds of semantic heterogeneities (name heterogeneity and structure heterogeneity) in spatial data service retrieval based on ontology, and also, based on the hierarchical subsumption relationship among concept in ontology, the query words can be extended and more resource can be matched and found for user. These applications of ontology in spatial data resource retrieval can help to improve the capability of keyword matching, and find more related resources.

  13. A framework for using reference ontologies as a foundation for the semantic web.

    Science.gov (United States)

    Brinkley, James F; Suciu, Dan; Detwiler, Landon T; Gennari, John H; Rosse, Cornelius

    2006-01-01

    The semantic web is envisioned as an evolving set of local ontologies that are gradually linked together into a global knowledge network. Many such local "application" ontologies are being built, but it is difficult to link them together because of incompatibilities and lack of adherence to ontology standards. "Reference" ontologies are an emerging ontology type that attempt to represent deep knowledge of basic science in a principled way that allows them to be re-used in multiple ways, just as the basic sciences are re-used in clinical applications. As such they have the potential to be a foundation for the semantic web if methods can be developed for deriving application ontologies from them. We describe a computational framework for this purpose that is generalized from the database concept of "views", and describe the research issues that must be solved to implement such a framework. We argue that the development of such a framework is becoming increasingly feasible due to a convergence of advances in several fields.

  14. A framework for unifying ontology-based semantic similarity measures: a study in the biomedical domain.

    Science.gov (United States)

    Harispe, Sébastien; Sánchez, David; Ranwez, Sylvie; Janaqi, Stefan; Montmain, Jacky

    2014-04-01

    Ontologies are widely adopted in the biomedical domain to characterize various resources (e.g. diseases, drugs, scientific publications) with non-ambiguous meanings. By exploiting the structured knowledge that ontologies provide, a plethora of ad hoc and domain-specific semantic similarity measures have been defined over the last years. Nevertheless, some critical questions remain: which measure should be defined/chosen for a concrete application? Are some of the, a priori different, measures indeed equivalent? In order to bring some light to these questions, we perform an in-depth analysis of existing ontology-based measures to identify the core elements of semantic similarity assessment. As a result, this paper presents a unifying framework that aims to improve the understanding of semantic measures, to highlight their equivalences and to propose bridges between their theoretical bases. By demonstrating that groups of measures are just particular instantiations of parameterized functions, we unify a large number of state-of-the-art semantic similarity measures through common expressions. The application of the proposed framework and its practical usefulness is underlined by an empirical analysis of hundreds of semantic measures in a biomedical context. Copyright © 2013 Elsevier Inc. All rights reserved.

  15. VuWiki: An Ontology-Based Semantic Wiki for Vulnerability Assessments

    Science.gov (United States)

    Khazai, Bijan; Kunz-Plapp, Tina; Büscher, Christian; Wegner, Antje

    2014-05-01

    The concept of vulnerability, as well as its implementation in vulnerability assessments, is used in various disciplines and contexts ranging from disaster management and reduction to ecology, public health or climate change and adaptation, and a corresponding multitude of ideas about how to conceptualize and measure vulnerability exists. Three decades of research in vulnerability have generated a complex and growing body of knowledge that challenges newcomers, practitioners and even experienced researchers. To provide a structured representation of the knowledge field "vulnerability assessment", we have set up an ontology-based semantic wiki for reviewing and representing vulnerability assessments: VuWiki, www.vuwiki.org. Based on a survey of 55 vulnerability assessment studies, we first developed an ontology as an explicit reference system for describing vulnerability assessments. We developed the ontology in a theoretically controlled manner based on general systems theory and guided by principles for ontology development in the field of earth and environment (Raskin and Pan 2005). Four key questions form the first level "branches" or categories of the developed ontology: (1) Vulnerability of what? (2) Vulnerability to what? (3) What reference framework was used in the vulnerability assessment?, and (4) What methodological approach was used in the vulnerability assessment? These questions correspond to the basic, abstract structure of the knowledge domain of vulnerability assessments and have been deduced from theories and concepts of various disciplines. The ontology was then implemented in a semantic wiki which allows for the classification and annotation of vulnerability assessments. As a semantic wiki, VuWiki does not aim at "synthesizing" a holistic and overarching model of vulnerability. Instead, it provides both scientists and practitioners with a uniform ontology as a reference system and offers easy and structured access to the knowledge field of

  16. Semantic information can facilitate covert face recognition in congenital prosopagnosia.

    Science.gov (United States)

    Rivolta, Davide; Schmalzl, Laura; Coltheart, Max; Palermo, Romina

    2010-11-01

    People with congenital prosopagnosia have never developed the ability to accurately recognize faces. This single case investigation systematically investigates covert and overt face recognition in "C.," a 69 year-old woman with congenital prosopagnosia. Specifically, we: (a) describe the first assessment of covert face recognition in congenital prosopagnosia using multiple tasks; (b) show that semantic information can contribute to covert recognition; and (c) provide a theoretical explanation for the mechanisms underlying covert face recognition.

  17. Semantic Richness Effects in Spoken Word Recognition: A Lexical Decision and Semantic Categorization Megastudy.

    Science.gov (United States)

    Goh, Winston D; Yap, Melvin J; Lau, Mabel C; Ng, Melvin M R; Tan, Luuan-Chin

    2016-01-01

    A large number of studies have demonstrated that semantic richness dimensions [e.g., number of features, semantic neighborhood density, semantic diversity , concreteness, emotional valence] influence word recognition processes. Some of these richness effects appear to be task-general, while others have been found to vary across tasks. Importantly, almost all of these findings have been found in the visual word recognition literature. To address this gap, we examined the extent to which these semantic richness effects are also found in spoken word recognition, using a megastudy approach that allows for an examination of the relative contribution of the various semantic properties to performance in two tasks: lexical decision, and semantic categorization. The results show that concreteness, valence, and number of features accounted for unique variance in latencies across both tasks in a similar direction-faster responses for spoken words that were concrete, emotionally valenced, and with a high number of features-while arousal, semantic neighborhood density, and semantic diversity did not influence latencies. Implications for spoken word recognition processes are discussed.

  18. MULTI MODAL ONTOLOGY SEARCH FOR SEMANTIC IMAGE RETRIEVAL

    Directory of Open Access Journals (Sweden)

    R.I. Minu

    2012-08-01

    Full Text Available In this world of fast computing, automation plays an important role. In image retrieval technique automation is a great quest. Giving an image as a query and retrieving relevant images is a challenging research area. In this paper we are proposing a research of using Multi-Modality Ontology integration for image retrieval concept. The core strategy in multimodal information retrieval is the combination or fusion of different data modalities to expand and complement information. Here we use both visual and textual ontology contents to provide search functionalities. Both images and texts are complimentary information units as the human perspective will be different. So, the computational linguistic of images will lead to disambiguate text meaning when it is not quite clear in right sense of several words. That’s why the Multi-Modal information retrieval may lead to an improved operation of information retrieval system. If we go for automation we are in need of a fuzzy technique to predicate the result. So in this paper we using Support Vector Machine classifier to classify the image automatically by using the general feature such as color, texture and texton of an image , then by using this result we can create both feature and domain ontology for an particular image. Using this Multi-Modality Ontology we can refine our image searching system.

  19. The environment ontology in 2016: bridging domains with increased scope, semantic density, and interoperation.

    Science.gov (United States)

    Buttigieg, Pier Luigi; Pafilis, Evangelos; Lewis, Suzanna E; Schildhauer, Mark P; Walls, Ramona L; Mungall, Christopher J

    2016-09-23

    The Environment Ontology (ENVO; http://www.environmentontology.org/ ), first described in 2013, is a resource and research target for the semantically controlled description of environmental entities. The ontology's initial aim was the representation of the biomes, environmental features, and environmental materials pertinent to genomic and microbiome-related investigations. However, the need for environmental semantics is common to a multitude of fields, and ENVO's use has steadily grown since its initial description. We have thus expanded, enhanced, and generalised the ontology to support its increasingly diverse applications. We have updated our development suite to promote expressivity, consistency, and speed: we now develop ENVO in the Web Ontology Language (OWL) and employ templating methods to accelerate class creation. We have also taken steps to better align ENVO with the Open Biological and Biomedical Ontologies (OBO) Foundry principles and interoperate with existing OBO ontologies. Further, we applied text-mining approaches to extract habitat information from the Encyclopedia of Life and automatically create experimental habitat classes within ENVO. Relative to its state in 2013, ENVO's content, scope, and implementation have been enhanced and much of its existing content revised for improved semantic representation. ENVO now offers representations of habitats, environmental processes, anthropogenic environments, and entities relevant to environmental health initiatives and the global Sustainable Development Agenda for 2030. Several branches of ENVO have been used to incubate and seed new ontologies in previously unrepresented domains such as food and agronomy. The current release version of the ontology, in OWL format, is available at http://purl.obolibrary.org/obo/envo.owl . ENVO has been shaped into an ontology which bridges multiple domains including biomedicine, natural and anthropogenic ecology, 'omics, and socioeconomic development. Through

  20. SEMANTIC WEB-BASED SOFTWARE ENGINEERING BY AUTOMATED REQUIREMENTS ONTOLOGY GENERATION IN SOA

    Directory of Open Access Journals (Sweden)

    Vahid Rastgoo

    2014-04-01

    Full Text Available This paper presents an approach for automated generation of requirements ontology using UML diagrams in service-oriented architecture (SOA. The goal of this paper is to convenience progress of software engineering processes like software design, software reuse, service discovering and etc. The proposed method is based on a four conceptual layers. The first layer includes requirements achieved by stakeholders, the second one designs service-oriented diagrams from the data in first layer and extracts XMI codes of them. The third layer includes requirement ontology and protocol ontology to describe behavior of services and relationships between them semantically. Finally the forth layer makes standard the concepts exists in ontologies of previous layer. The generated ontology exceeds absolute domain ontology because it considers the behavior of services moreover the hierarchical relationship of them. Experimental results conducted on a set of UML4Soa diagrams in different scopes demonstrate the improvement of the proposed approach from different points of view such as: completeness of requirements ontology, automatic generation and considering SOA.

  1. Taxonomy, Ontology and Semantics at Johnson Space Center

    Science.gov (United States)

    Berndt, Sarah Ann

    2011-01-01

    At NASA Johnson Space Center (JSC), the Chief Knowledge Officer has been developing the JSC Taxonomy to capitalize on the accomplishments of yesterday while maintaining the flexibility needed for the evolving information environment of today. A clear vision and scope for the semantic system is integral to its success. The vision for the JSC Taxonomy is to connect information stovepipes to present a unified view for information and knowledge across the Center, across organizations, and across decades. Semantic search at JSC means seemless integration of disparate information sets into a single interface. Ever increasing use, interest, and organizational participation mark successful integration and provide the framework for future application.

  2. Semantic similarity from natural language and ontology analysis

    CERN Document Server

    Harispe, Sébastien; Janaqi, Stefan

    2015-01-01

    Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli.In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances def

  3. Semantic Modeling of Requirements: Leveraging Ontologies in Systems Engineering

    Science.gov (United States)

    Mir, Masood Saleem

    2012-01-01

    The interdisciplinary nature of "Systems Engineering" (SE), having "stakeholders" from diverse domains with orthogonal facets, and need to consider all stages of "lifecycle" of system during conception, can benefit tremendously by employing "Knowledge Engineering" (KE) to achieve semantic agreement among all…

  4. Semantic Modeling of Requirements: Leveraging Ontologies in Systems Engineering

    Science.gov (United States)

    Mir, Masood Saleem

    2012-01-01

    The interdisciplinary nature of "Systems Engineering" (SE), having "stakeholders" from diverse domains with orthogonal facets, and need to consider all stages of "lifecycle" of system during conception, can benefit tremendously by employing "Knowledge Engineering" (KE) to achieve semantic agreement among all…

  5. Ontology-based improvement to human activity recognition

    Science.gov (United States)

    Tahmoush, David; Bonial, Claire

    2016-05-01

    Human activity recognition has often prioritized low-level features extracted from imagery or video over higher-level class attributes and ontologies because they have traditionally been more effective on small datasets. However, by including knowledge-driven associations between actions and attributes while recognizing the lower-level attributes with their temporal relationships, we can attempt a hybrid approach that is more easily extensible to much larger datasets. We demonstrate a combination of hard and soft features with a comparison factor that prioritizes one approach over the other with a relative weight. We then exhaustively search over the comparison factor to evaluate the performance of a hybrid human activity recognition approach in comparison to the base hard approach at 84% accuracy and the current state-of-the-art.

  6. A Domain Specific Ontology Based Semantic Web Search Engine

    CERN Document Server

    Mukhopadhyay, Debajyoti; Mukherjee, Sreemoyee; Bhattacharya, Jhilik; Kim, Young-Chon

    2011-01-01

    Since its emergence in the 1990s the World Wide Web (WWW) has rapidly evolved into a huge mine of global information and it is growing in size everyday. The presence of huge amount of resources on the Web thus poses a serious problem of accurate search. This is mainly because today's Web is a human-readable Web where information cannot be easily processed by machine. Highly sophisticated, efficient keyword based search engines that have evolved today have not been able to bridge this gap. So comes up the concept of the Semantic Web which is envisioned by Tim Berners-Lee as the Web of machine interpretable information to make a machine processable form for expressing information. Based on the semantic Web technologies we present in this paper the design methodology and development of a semantic Web search engine which provides exact search results for a domain specific search. This search engine is developed for an agricultural Website which hosts agricultural information about the state of West Bengal.

  7. A Novel Mobile Video Community Discovery Scheme Using Ontology-Based Semantical Interest Capture

    Directory of Open Access Journals (Sweden)

    Ruiling Zhang

    2016-01-01

    Full Text Available Leveraging network virtualization technologies, the community-based video systems rely on the measurement of common interests to define and steady relationship between community members, which promotes video sharing performance and improves scalability community structure. In this paper, we propose a novel mobile Video Community discovery scheme using ontology-based semantical interest capture (VCOSI. An ontology-based semantical extension approach is proposed, which describes video content and measures video similarity according to video key word selection methods. In order to reduce the calculation load of video similarity, VCOSI designs a prefix-filtering-based estimation algorithm to decrease energy consumption of mobile nodes. VCOSI further proposes a member relationship estimate method to construct scalable and resilient node communities, which promotes video sharing capacity of video systems with the flexible and economic community maintenance. Extensive tests show how VCOSI obtains better performance results in comparison with other state-of-the-art solutions.

  8. Semantic-ontological combination of Business Rules and Business Processes in IT Service Management

    CERN Document Server

    Sellner, Alexander; Zinser, Erwin

    2011-01-01

    IT Service Management deals with managing a broad range of items related to complex system environments. As there is both, a close connection to business interests and IT infrastructure, the application of semantic expressions which are seamlessly integrated within applications for managing ITSM environments, can help to improve transparency and profitability. This paper focuses on the challenges regarding the integration of semantics and ontologies within ITSM environments. It will describe the paradigm of relationships and inheritance within complex service trees and will present an approach of ontologically expressing them. Furthermore, the application of SBVR-based rules as executable SQL triggers will be discussed. Finally, the broad range of topics for further research, derived from the findings, will be presented.

  9. The effects of shared information on semantic calculations in the gene ontology.

    Science.gov (United States)

    Bible, Paul W; Sun, Hong-Wei; Morasso, Maria I; Loganantharaj, Rasiah; Wei, Lai

    2017-01-01

    The structured vocabulary that describes gene function, the gene ontology (GO), serves as a powerful tool in biological research. One application of GO in computational biology calculates semantic similarity between two concepts to make inferences about the functional similarity of genes. A class of term similarity algorithms explicitly calculates the shared information (SI) between concepts then substitutes this calculation into traditional term similarity measures such as Resnik, Lin, and Jiang-Conrath. Alternative SI approaches, when combined with ontology choice and term similarity type, lead to many gene-to-gene similarity measures. No thorough investigation has been made into the behavior, complexity, and performance of semantic methods derived from distinct SI approaches. We apply bootstrapping to compare the generalized performance of 57 gene-to-gene semantic measures across six benchmarks. Considering the number of measures, we additionally evaluate whether these methods can be leveraged through ensemble machine learning to improve prediction performance. Results showed that the choice of ontology type most strongly influenced performance across all evaluations. Combining measures into an ensemble classifier reduces cross-validation error beyond any individual measure for protein interaction prediction. This improvement resulted from information gained through the combination of ontology types as ensemble methods within each GO type offered no improvement. These results demonstrate that multiple SI measures can be leveraged for machine learning tasks such as automated gene function prediction by incorporating methods from across the ontologies. To facilitate future research in this area, we developed the GO Graph Tool Kit (GGTK), an open source C++ library with Python interface (github.com/paulbible/ggtk).

  10. A Semantic Social Recommender System Using Ontologies Based Approach For Tunisian Tourism

    Directory of Open Access Journals (Sweden)

    Mohamed FRIKHA

    2015-12-01

    Full Text Available Tunisia is well placed in terms of medical tourism and has highly qualified and specialized medical and surgical teams. Integrating social networks in Tunisian medical tourism recommender systems can result in much more accurate recommendations. That is to say, information, interests, and recommendations retrieved from social networks can improve the prediction accuracy. This paper aims to improve traditional recommender systems by incorporating information in social network; including user preferences and influences from social friends. Accordingly, a user interest ontology is developed to make personalized recommendations out of such information. In this paper, we present a semantic social recommender system employing a user interest ontology and a Tunisian Medical Tourism ontology. Our system can improve the quality of recommendation for Tunisian tourism domain. Finally, our social recommendation algorithm is implemented in order to be used in a Tunisia tourism Website to assist users interested in visiting Tunisia for medical purposes.

  11. Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

    Science.gov (United States)

    Liang, Chen; Sun, Jingchun; Tao, Cui

    2015-01-01

    There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

  12. Inferring the semantic relationships of words within an ontology using random indexing: applications to pharmacogenomics.

    Science.gov (United States)

    Percha, Bethany; Altman, Russ B

    2013-01-01

    The biomedical literature presents a uniquely challenging text mining problem. Sentences are long and complex, the subject matter is highly specialized with a distinct vocabulary, and producing annotated training data for this domain is time consuming and expensive. In this environment, unsupervised text mining methods that do not rely on annotated training data are valuable. Here we investigate the use of random indexing, an automated method for producing vector-space semantic representations of words from large, unlabeled corpora, to address the problem of term normalization in sentences describing drugs and genes. We show that random indexing produces similarity scores that capture some of the structure of PHARE, a manually curated ontology of pharmacogenomics concepts. We further show that random indexing can be used to identify likely word candidates for inclusion in the ontology, and can help localize these new labels among classes and roles within the ontology.

  13. Validating the semantics of a medical iconic language using ontological reasoning.

    Science.gov (United States)

    Lamy, Jean-Baptiste; Soualmia, Lina F; Kerdelhué, Gaëtan; Venot, Alain; Duclos, Catherine

    2013-02-01

    To help clinicians read medical texts such as clinical practice guidelines or drug monographs, we proposed an iconic language called VCM. This language can use icons to represent the main medical concepts, including diseases, symptoms, treatments and follow-up procedures, by combining various pictograms, shapes and colors. However, the semantics of this language have not been formalized, and users may create inconsistent icons, e.g. by combining the "tumor" shape and the "sleeping" pictograms into a "tumor of sleeping" icon. This work aims to represent the VCM language using DLs and OWL for evaluating its semantics by reasoners, and in particular for determining inconsistent icons. We designed an ontology for formalized the semantics of VCM icons using the Protégé editor and scripts for translating the VCM lexicon in OWL. We evaluated the ability of the ontology to determine icon consistency for a set of 100 random icons. The evaluation showed good results for determining icon consistency, with a high sensitivity. The ontology may also be useful for the design of mapping between VCM and other medical terminologies, for generating textual labels for icons, and for developing user interfaces for creating VCM icons.

  14. The chemical information ontology: provenance and disambiguation for chemical data on the biological semantic web.

    Science.gov (United States)

    Hastings, Janna; Chepelev, Leonid; Willighagen, Egon; Adams, Nico; Steinbeck, Christoph; Dumontier, Michel

    2011-01-01

    Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA).

  15. The chemical information ontology: provenance and disambiguation for chemical data on the biological semantic web.

    Directory of Open Access Journals (Sweden)

    Janna Hastings

    Full Text Available Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA.

  16. Protein-protein interaction inference based on semantic similarity of Gene Ontology terms.

    Science.gov (United States)

    Zhang, Shu-Bo; Tang, Qiang-Rong

    2016-07-21

    Identifying protein-protein interactions is important in molecular biology. Experimental methods to this issue have their limitations, and computational approaches have attracted more and more attentions from the biological community. The semantic similarity derived from the Gene Ontology (GO) annotation has been regarded as one of the most powerful indicators for protein interaction. However, conventional methods based on GO similarity fail to take advantage of the specificity of GO terms in the ontology graph. We proposed a GO-based method to predict protein-protein interaction by integrating different kinds of similarity measures derived from the intrinsic structure of GO graph. We extended five existing methods to derive the semantic similarity measures from the descending part of two GO terms in the GO graph, then adopted a feature integration strategy to combines both the ascending and the descending similarity scores derived from the three sub-ontologies to construct various kinds of features to characterize each protein pair. Support vector machines (SVM) were employed as discriminate classifiers, and five-fold cross validation experiments were conducted on both human and yeast protein-protein interaction datasets to evaluate the performance of different kinds of integrated features, the experimental results suggest the best performance of the feature that combines information from both the ascending and the descending parts of the three ontologies. Our method is appealing for effective prediction of protein-protein interaction.

  17. Recognition of spoken words: semantic effects in lexical access.

    Science.gov (United States)

    Wurm, Lee H; Vakoch, Douglas A; Seaman, Sean R

    2004-01-01

    Until recently most models of word recognition have assumed that semantic auditory naming effects come into play only after the identification of the word in question. What little evidence exists for early semantic effects in word recognition lexical decision has relied primarily on priming manipulations using the lexical decision task, and has used visual stimulus presentation. The current study uses semantics auditory stimulus presentation and multiple experimental tasks, and does not use priming. Response latencies for 100 common nouns were found to speech perception depend on perceptual dimensions identified by Osgood (1969): Evaluation, Potency, and Activity. In addition, the two-way interactions between these word recognition dimensions were significant. All effects were above and beyond the effects of concreteness, word length, frequency, onset phoneme characteristics, stress, and neighborhood density. Results are discussed against evidence from several areas of research suggesting a role of behaviorally important information in perception.

  18. The Ontological Perspectives of the Semantic Web and the Metadata Harvesting Protocol: Applications of Metadata for Improving Web Search.

    Science.gov (United States)

    Fast, Karl V.; Campbell, D. Grant

    2001-01-01

    Compares the implied ontological frameworks of the Open Archives Initiative Protocol for Metadata Harvesting and the World Wide Web Consortium's Semantic Web. Discusses current search engine technology, semantic markup, indexing principles of special libraries and online databases, and componentization and the distinction between data and…

  19. Robust place recognition with an application to semantic topological mapping

    Science.gov (United States)

    Siddiqui, J. R.; Khatibi, S.

    2013-12-01

    The problem of robust and invariant representation of places is being addressed. A place recognition technique is proposed followed by an application to a semantic topological mapping. The proposed technique is evaluated on a robot localization database which consists of a large set of images taken under various weather conditions. The results show that the proposed method can robustly recognize the places and is invariant to geometric transformations, brightness changes and noise. The comparative analysis with the state-of-the-art semantic place description methods show that the method outperforms the competing methods and exhibits better average recognition rates.

  20. A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

    Science.gov (United States)

    Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

    2016-02-01

    Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. A semantic web ontology for small molecules and their biological targets.

    Science.gov (United States)

    Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

    2010-05-24

    A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

  2. On combining image-based and ontological semantic dissimilarities for medical image retrieval applications.

    Science.gov (United States)

    Kurtz, Camille; Depeursinge, Adrien; Napel, Sandy; Beaulieu, Christopher F; Rubin, Daniel L

    2014-10-01

    Computer-assisted image retrieval applications can assist radiologists by identifying similar images in archives as a means to providing decision support. In the classical case, images are described using low-level features extracted from their contents, and an appropriate distance is used to find the best matches in the feature space. However, using low-level image features to fully capture the visual appearance of diseases is challenging and the semantic gap between these features and the high-level visual concepts in radiology may impair the system performance. To deal with this issue, the use of semantic terms to provide high-level descriptions of radiological image contents has recently been advocated. Nevertheless, most of the existing semantic image retrieval strategies are limited by two factors: they require manual annotation of the images using semantic terms and they ignore the intrinsic visual and semantic relationships between these annotations during the comparison of the images. Based on these considerations, we propose an image retrieval framework based on semantic features that relies on two main strategies: (1) automatic "soft" prediction of ontological terms that describe the image contents from multi-scale Riesz wavelets and (2) retrieval of similar images by evaluating the similarity between their annotations using a new term dissimilarity measure, which takes into account both image-based and ontological term relations. The combination of these strategies provides a means of accurately retrieving similar images in databases based on image annotations and can be considered as a potential solution to the semantic gap problem. We validated this approach in the context of the retrieval of liver lesions from computed tomographic (CT) images and annotated with semantic terms of the RadLex ontology. The relevance of the retrieval results was assessed using two protocols: evaluation relative to a dissimilarity reference standard defined for pairs of

  3. Semantic – Based Querying Using Ontology in Relational Database of Library Management System

    Directory of Open Access Journals (Sweden)

    Ayesha Banu

    2011-11-01

    Full Text Available The traditional Web stores huge amount of data in the form of Relational Databases (RDB as it is good atstoring objects and relationships between them. Relational Databases are dynamic in nature which allowsbringing tables together helping user to search for related material across multiple tables. RDB arescalable to expand as the data grows. The RDB uses a Structured Query Language called SQL to accessthe databases for several data retrieval purposes. As the world is moving today from the Syntactic form toSemantic form and the Web is also taking its new form of Semantic Web. The Structured Query of the RDBon web can be a Semantic Query on Semantic Web. The SPARQL is the Query Language recommended byW3C for the RDF(Resource Description Framework. RDF is a directed, labeled graph data format forrepresenting information in the Web and is a very important layer of the Semantic Web Architecture. In thispaper we consider the Library Management System (LMS database, taking some tuples of the LMSRelational Schema. We discuss how the RDF code is scripted and validated using RDF Validator and howRDF Triples are generated. Later we give the graphical representation of the RDF triples and see theprocess of extracting ontology from the RDF Schema and application of the Semantic Query.

  4. Utilizing Statistical Semantic Similarity Techniques for Ontology Mapping——with Applications to AEC Standard Models

    Institute of Scientific and Technical Information of China (English)

    Pan Jiayi; Chin-Pang Jack Cheng; Gloria T. Lau; Kincho H. Law

    2008-01-01

    The objective of this paper is to introduce three semi-automated approaches for ontology mapping using relatedness analysis techniques. In the architecture, engineering, and construction (AEC) industry, there exist a number of ontological standards to describe the semantics of building models. Although the standards share similar scopes of interest, the task of comparing and mapping concepts among standards is challenging due to their differences in terminologies and perspectives. Ontology mapping is therefore necessary to achieve information interoperability, which allows two or more information sources to exchange data and to re-use the data for further purposes. The attribute-based approach, corpus-based approach, and name-based approach presented in this paper adopt the statistical relatedness analysis techniques to discover related concepts from heterogeneous ontologies. A pilot study is conducted on IFC and CIS/2 ontologies to evaluate the approaches. Preliminary results show that the attribute-based approach outperforms the other two approaches in terms of precision and F-measure.

  5. An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology

    Directory of Open Access Journals (Sweden)

    Jain Shobhit

    2010-11-01

    Full Text Available Abstract Background Semantic similarity measures are useful to assess the physiological relevance of protein-protein interactions (PPIs. They quantify similarity between proteins based on their function using annotation systems like the Gene Ontology (GO. Proteins that interact in the cell are likely to be in similar locations or involved in similar biological processes compared to proteins that do not interact. Thus the more semantically similar the gene function annotations are among the interacting proteins, more likely the interaction is physiologically relevant. However, most semantic similarity measures used for PPI confidence assessment do not consider the unequal depth of term hierarchies in different classes of cellular location, molecular function, and biological process ontologies of GO and thus may over-or under-estimate similarity. Results We describe an improved algorithm, Topological Clustering Semantic Similarity (TCSS, to compute semantic similarity between GO terms annotated to proteins in interaction datasets. Our algorithm, considers unequal depth of biological knowledge representation in different branches of the GO graph. The central idea is to divide the GO graph into sub-graphs and score PPIs higher if participating proteins belong to the same sub-graph as compared to if they belong to different sub-graphs. Conclusions The TCSS algorithm performs better than other semantic similarity measurement techniques that we evaluated in terms of their performance on distinguishing true from false protein interactions, and correlation with gene expression and protein families. We show an average improvement of 4.6 times the F1 score over Resnik, the next best method, on our Saccharomyces cerevisiae PPI dataset and 2 times on our Homo sapiens PPI dataset using cellular component, biological process and molecular function GO annotations.

  6. Novel Ontologies-based Optical Character Recognition-error Correction Cooperating with Graph Component Extraction

    Directory of Open Access Journals (Sweden)

    Sarunya Kanjanawattana

    2017-01-01

    Full Text Available literature. Extracting graph information clearly contributes to readers, who are interested in graph information interpretation, because we can obtain significant information presenting in the graph. A typical tool used to transform image-based characters to computer editable characters is optical character recognition (OCR. Unfortunately, OCR cannot guarantee perfect results, because it is sensitive to noise and input quality. This becomes a serious problem because misrecognition provides misunderstanding information to readers and causes misleading communication. In this study, we present a novel method for OCR-error correction based on bar graphs using semantics, such as ontologies and dependency parsing. Moreover, we used a graph component extraction proposed in our previous study to omit irrelevant parts from graph components. It was applied to clean and prepare input data for this OCR-error correction. The main objectives of this paper are to extract significant information from the graph using OCR and to correct OCR errors using semantics. As a result, our method provided remarkable performance with the highest accuracies and F-measures. Moreover, we examined that our input data contained less of noise because of an efficiency of our graph component extraction. Based on the evidence, we conclude that our solution to the OCR problem achieves the objectives.

  7. KaBOB: ontology-based semantic integration of biomedical databases.

    Science.gov (United States)

    Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

    2015-04-23

    The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for

  8. Relevant Pages in semantic Web Search Engines using Ontology

    Directory of Open Access Journals (Sweden)

    Jemimah Simon

    2012-03-01

    Full Text Available In general, search engines are the most popular means of searching any kind of information from the Internet. Generally, keywords are given to the search engine and the Web database returns the documents containing specified keywords. In many situations, irrelevant results are given as results to the user query since different keywords are used in different forms in various documents. The development of the next generation Web, Semantic Web, will change this situation. This paper proposes a prototype of relation-based search engine which ranks the page according to the user query and on annotated results. Page sub graph is computed for each annotated page in the result set by generating all possible combinations for the relation in the sub graph. A relevance score is computed for each annotated page using a probability measure. A relation based ranking model is used which displays the pages in the final result set according to their relevance score. This ranking is provided by considering keyword-concept associations. Thus, the final result set contains pages in the order of their constrained relevant scores.

  9. Handling Real-World Context Awareness, Uncertainty and Vagueness in Real-Time Human Activity Tracking and Recognition with a Fuzzy Ontology-Based Hybrid Method

    Directory of Open Access Journals (Sweden)

    Natalia Díaz-Rodríguez

    2014-09-01

    Full Text Available Human activity recognition is a key task in ambient intelligence applications to achieve proper ambient assisted living. There has been remarkable progress in this domain, but some challenges still remain to obtain robust methods. Our goal in this work is to provide a system that allows the modeling and recognition of a set of complex activities in real life scenarios involving interaction with the environment. The proposed framework is a hybrid model that comprises two main modules: a low level sub-activity recognizer, based on data-driven methods, and a high-level activity recognizer, implemented with a fuzzy ontology to include the semantic interpretation of actions performed by users. The fuzzy ontology is fed by the sub-activities recognized by the low level data-driven component and provides fuzzy ontological reasoning to recognize both the activities and their influence in the environment with semantics. An additional benefit of the approach is the ability to handle vagueness and uncertainty in the knowledge-based module, which substantially outperforms the treatment of incomplete and/or imprecise data with respect to classic crisp ontologies. We validate these advantages with the public CAD-120 dataset (Cornell Activity Dataset, achieving an accuracy of 90.1% and 91.07% for low-level and high-level activities, respectively. This entails an improvement over fully data-driven or ontology-based approaches.

  10. Congruent and Incongruent Semantic Context Influence Vowel Recognition

    Science.gov (United States)

    Wotton, J. M.; Elvebak, R. L.; Moua, L. C.; Heggem, N. M.; Nelson, C. A.; Kirk, K. M.

    2011-01-01

    The influence of sentence context on the recognition of naturally spoken vowels degraded by reverberation and Gaussian noise was investigated. Target words were paired to have similar consonant sounds but different vowels (e.g., map/mop) and were embedded early in sentences which provided three types of semantic context. Fifty-eight…

  11. Deep Fusion of Multiple Semantic Cues for Complex Event Recognition.

    Science.gov (United States)

    Zhang, Xishan; Zhang, Hanwang; Zhang, Yongdong; Yang, Yang; Wang, Meng; Luan, Huanbo; Li, Jintao; Chua, Tat-Seng

    2016-03-01

    We present a deep learning strategy to fuse multiple semantic cues for complex event recognition. In particular, we tackle the recognition task by answering how to jointly analyze human actions (who is doing what), objects (what), and scenes (where). First, each type of semantic features (e.g., human action trajectories) is fed into a corresponding multi-layer feature abstraction pathway, followed by a fusion layer connecting all the different pathways. Second, the correlations of how the semantic cues interacting with each other are learned in an unsupervised cross-modality autoencoder fashion. Finally, by fine-tuning a large-margin objective deployed on this deep architecture, we are able to answer the question on how the semantic cues of who, what, and where compose a complex event. As compared with the traditional feature fusion methods (e.g., various early or late strategies), our method jointly learns the essential higher level features that are most effective for fusion and recognition. We perform extensive experiments on two real-world complex event video benchmarks, MED'11 and CCV, and demonstrate that our method outperforms the best published results by 21% and 11%, respectively, on an event recognition task.

  12. Web Video Event Recognition by Semantic Analysis From Ubiquitous Documents.

    Science.gov (United States)

    Yu, Litao; Yang, Yang; Huang, Zi; Wang, Peng; Song, Jingkuan; Shen, Heng Tao

    2016-12-01

    In recent years, the task of event recognition from videos has attracted increasing interest in multimedia area. While most of the existing research was mainly focused on exploring visual cues to handle relatively small-granular events, it is difficult to directly analyze video content without any prior knowledge. Therefore, synthesizing both the visual and semantic analysis is a natural way for video event understanding. In this paper, we study the problem of Web video event recognition, where Web videos often describe large-granular events and carry limited textual information. Key challenges include how to accurately represent event semantics from incomplete textual information and how to effectively explore the correlation between visual and textual cues for video event understanding. We propose a novel framework to perform complex event recognition from Web videos. In order to compensate the insufficient expressive power of visual cues, we construct an event knowledge base by deeply mining semantic information from ubiquitous Web documents. This event knowledge base is capable of describing each event with comprehensive semantics. By utilizing this base, the textual cues for a video can be significantly enriched. Furthermore, we introduce a two-view adaptive regression model, which explores the intrinsic correlation between the visual and textual cues of the videos to learn reliable classifiers. Extensive experiments on two real-world video data sets show the effectiveness of our proposed framework and prove that the event knowledge base indeed helps improve the performance of Web video event recognition.

  13. Advancing data reuse in phyloinformatics using an ontology-driven Semantic Web approach.

    Science.gov (United States)

    Panahiazar, Maryam; Sheth, Amit P; Ranabahu, Ajith; Vos, Rutger A; Leebens-Mack, Jim

    2013-01-01

    Phylogenetic analyses can resolve historical relationships among genes, organisms or higher taxa. Understanding such relationships can elucidate a wide range of biological phenomena, including, for example, the importance of gene and genome duplications in the evolution of gene function, the role of adaptation as a driver of diversification, or the evolutionary consequences of biogeographic shifts. Phyloinformaticists are developing data standards, databases and communication protocols (e.g. Application Programming Interfaces, APIs) to extend the accessibility of gene trees, species trees, and the metadata necessary to interpret these trees, thus enabling researchers across the life sciences to reuse phylogenetic knowledge. Specifically, Semantic Web technologies are being developed to make phylogenetic knowledge interpretable by web agents, thereby enabling intelligently automated, high-throughput reuse of results generated by phylogenetic research. This manuscript describes an ontology-driven, semantic problem-solving environment for phylogenetic analyses and introduces artefacts that can promote phyloinformatic efforts to promote accessibility of trees and underlying metadata. PhylOnt is an extensible ontology with concepts describing tree types and tree building methodologies including estimation methods, models and programs. In addition we present the PhylAnt platform for annotating scientific articles and NeXML files with PhylOnt concepts. The novelty of this work is the annotation of NeXML files and phylogenetic related documents with PhylOnt Ontology. This approach advances data reuse in phyloinformatics.

  14. Information content-based gene ontology semantic similarity approaches: toward a unified framework theory.

    Science.gov (United States)

    Mazandu, Gaston K; Mulder, Nicola J

    2013-01-01

    Several approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG). These approaches contributed to improving protein analyses at the functional level. Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches. We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures. We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric. Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration. This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches. The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term's specificity in the GO DAG.

  15. Information Content-Based Gene Ontology Semantic Similarity Approaches: Toward a Unified Framework Theory

    Science.gov (United States)

    Mazandu, Gaston K.; Mulder, Nicola J.

    2013-01-01

    Several approaches have been proposed for computing term information content (IC) and semantic similarity scores within the gene ontology (GO) directed acyclic graph (DAG). These approaches contributed to improving protein analyses at the functional level. Considering the recent proliferation of these approaches, a unified theory in a well-defined mathematical framework is necessary in order to provide a theoretical basis for validating these approaches. We review the existing IC-based ontological similarity approaches developed in the context of biomedical and bioinformatics fields to propose a general framework and unified description of all these measures. We have conducted an experimental evaluation to assess the impact of IC approaches, different normalization models, and correction factors on the performance of a functional similarity metric. Results reveal that considering only parents or only children of terms when assessing information content or semantic similarity scores negatively impacts the approach under consideration. This study produces a unified framework for current and future GO semantic similarity measures and provides theoretical basics for comparing different approaches. The experimental evaluation of different approaches based on different term information content models paves the way towards a solution to the issue of scoring a term's specificity in the GO DAG. PMID:24078912

  16. Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

    Directory of Open Access Journals (Sweden)

    Carlos R. Rangel

    2016-08-01

    Full Text Available In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease, and the main cells in each community. We analyze our approach in two cases: TGF-ß and the Alzheimer Disease.

  17. Terminology representation guidelines for biomedical ontologies in the semantic web notations.

    Science.gov (United States)

    Tao, Cui; Pathak, Jyotishman; Solbrig, Harold R; Wei, Wei-Qi; Chute, Christopher G

    2013-02-01

    Terminologies and ontologies are increasingly prevalent in healthcare and biomedicine. However they suffer from inconsistent renderings, distribution formats, and syntax that make applications through common terminologies services challenging. To address the problem, one could posit a shared representation syntax, associated schema, and tags. We identified a set of commonly-used elements in biomedical ontologies and terminologies based on our experience with the Common Terminology Services 2 (CTS2) Specification as well as the Lexical Grid (LexGrid) project. We propose guidelines for precisely such a shared terminology model, and recommend tags assembled from SKOS, OWL, Dublin Core, RDF Schema, and DCMI meta-terms. We divide these guidelines into lexical information (e.g. synonyms, and definitions) and semantic information (e.g. hierarchies). The latter we distinguish for use by informal terminologies vs. formal ontologies. We then evaluate the guidelines with a spectrum of widely used terminologies and ontologies to examine how the lexical guidelines are implemented, and whether our proposed guidelines would enhance interoperability.

  18. Desiderata for ontologies to be used in semantic annotation of biomedical documents.

    Science.gov (United States)

    Bada, Michael; Hunter, Lawrence

    2011-02-01

    A wealth of knowledge valuable to the translational research scientist is contained within the vast biomedical literature, but this knowledge is typically in the form of natural language. Sophisticated natural-language-processing systems are needed to translate text into unambiguous formal representations grounded in high-quality consensus ontologies, and these systems in turn rely on gold-standard corpora of annotated documents for training and testing. To this end, we are constructing the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-text biomedical journal articles that are being manually annotated with the entire sets of terms from select vocabularies, predominantly from the Open Biomedical Ontologies (OBO) library. Our efforts in building this corpus has illuminated infelicities of these ontologies with respect to the semantic annotation of biomedical documents, and we propose desiderata whose implementation could substantially improve their utility in this task; these include the integration of overlapping terms across OBOs, the resolution of OBO-specific ambiguities, the integration of the BFO with the OBOs and the use of mid-level ontologies, the inclusion of noncanonical instances, and the expansion of relations and realizable entities.

  19. Lexical-Semantic Processing and Reading: Relations between Semantic Priming, Visual Word Recognition and Reading Comprehension

    Science.gov (United States)

    Nobre, Alexandre de Pontes; de Salles, Jerusa Fumagalli

    2016-01-01

    The aim of this study was to investigate relations between lexical-semantic processing and two components of reading: visual word recognition and reading comprehension. Sixty-eight children from private schools in Porto Alegre, Brazil, from 7 to 12 years, were evaluated. Reading was assessed with a word/nonword reading task and a reading…

  20. Lexical-Semantic Processing and Reading: Relations between Semantic Priming, Visual Word Recognition and Reading Comprehension

    Science.gov (United States)

    Nobre, Alexandre de Pontes; de Salles, Jerusa Fumagalli

    2016-01-01

    The aim of this study was to investigate relations between lexical-semantic processing and two components of reading: visual word recognition and reading comprehension. Sixty-eight children from private schools in Porto Alegre, Brazil, from 7 to 12 years, were evaluated. Reading was assessed with a word/nonword reading task and a reading…

  1. A revision of Evaniscus (Hymenoptera, Evaniidae using ontology-based semantic phenotype annotation

    Directory of Open Access Journals (Sweden)

    Patricia Mullins

    2012-09-01

    Full Text Available The Neotropical evaniid genus Evaniscus Szépligeti currently includes six species. Two new species are described, Evaniscus lansdownei Mullins, sp. n. from Colombia and Brazil and E. rafaeli Kawada, sp. n. from Brazil. Evaniscus sulcigenis Roman, syn. n., is synonymized under E. rufithorax Enderlein. An identification key to species of Evaniscus is provided. Thirty-five parsimony informative morphological characters are analyzed for six ingroup and four outgroup taxa. A topology resulting in a monophyletic Evaniscus is presented with E. tibialis and E. rafaeli as sister to the remaining Evaniscus species. The Hymenoptera Anatomy Ontology and other relevant biomedical ontologies are employed to create semantic phenotype statements in Entity-Quality (EQ format for species descriptions. This approach is an early effort to formalize species descriptions and to make descriptive data available to other domains.

  2. A revision of Evaniscus (Hymenoptera, Evaniidae) using ontology-based semantic phenotype annotation.

    Science.gov (United States)

    Mullins, Patricia L; Kawada, Ricardo; Balhoff, James P; Deans, Andrew R

    2012-01-01

    The Neotropical evaniid genus Evaniscus Szépligeti currently includes six species. Two new species are described, Evaniscus lansdownei Mullins, sp. n. from Colombia and Brazil and Evaniscus rafaeli Kawada, sp. n. from Brazil. Evaniscus sulcigenis Roman, syn. n., is synonymized under Evaniscus rufithorax Enderlein. An identification key to species of Evaniscus is provided. Thirty-five parsimony informative morphological characters are analyzed for six ingroup and four outgroup taxa. A topology resulting in a monophyletic Evaniscus is presented with Evaniscus tibialis and Evaniscus rafaeli as sister to the remaining Evaniscus species. The Hymenoptera Anatomy Ontology and other relevant biomedical ontologies are employed to create semantic phenotype statements in Entity-Quality (EQ) format for species descriptions. This approach is an early effort to formalize species descriptions and to make descriptive data available to other domains.

  3. Ontology-Based Annotation of Multimedia Language Data for the Semantic Web

    CERN Document Server

    Chebotko, Artem; Fotouhi, Farshad; Aristar, Anthony

    2009-01-01

    There is an increasing interest and effort in preserving and documenting endangered languages. Language data are valuable only when they are well-cataloged, indexed and searchable. Many language data, particularly those of lesser-spoken languages, are collected as audio and video recordings. While multimedia data provide more channels and dimensions to describe a language's function, and gives a better presentation of the cultural system associated with the language of that community, they are not text-based or structured (in binary format), and their semantics is implicit in their content. The content is thus easy for a human being to understand, but difficult for computers to interpret. Hence, there is a great need for a powerful and user-friendly system to annotate multimedia data with text-based, well-structured and searchable metadata. This chapter describes an ontology-based multimedia annotation tool, OntoELAN, that enables annotation of language multimedia data with a linguistic ontology.

  4. BioAssay Ontology (BAO: a semantic description of bioassays and high-throughput screening results

    Directory of Open Access Journals (Sweden)

    Smith Robin P

    2011-06-01

    Full Text Available Abstract Background High-throughput screening (HTS is one of the main strategies to identify novel entry points for the development of small molecule chemical probes and drugs and is now commonly accessible to public sector research. Large amounts of data generated in HTS campaigns are submitted to public repositories such as PubChem, which is growing at an exponential rate. The diversity and quantity of available HTS assays and screening results pose enormous challenges to organizing, standardizing, integrating, and analyzing the datasets and thus to maximize the scientific and ultimately the public health impact of the huge investments made to implement public sector HTS capabilities. Novel approaches to organize, standardize and access HTS data are required to address these challenges. Results We developed the first ontology to describe HTS experiments and screening results using expressive description logic. The BioAssay Ontology (BAO serves as a foundation for the standardization of HTS assays and data and as a semantic knowledge model. In this paper we show important examples of formalizing HTS domain knowledge and we point out the advantages of this approach. The ontology is available online at the NCBO bioportal http://bioportal.bioontology.org/ontologies/44531. Conclusions After a large manual curation effort, we loaded BAO-mapped data triples into a RDF database store and used a reasoner in several case studies to demonstrate the benefits of formalized domain knowledge representation in BAO. The examples illustrate semantic querying capabilities where BAO enables the retrieval of inferred search results that are relevant to a given query, but are not explicitly defined. BAO thus opens new functionality for annotating, querying, and analyzing HTS datasets and the potential for discovering new knowledge by means of inference.

  5. Building Rules on Top of Ontologies for the Semantic Web with Inductive Logic Programming

    OpenAIRE

    Lisi, Francesca A.

    2007-01-01

    Building rules on top of ontologies is the ultimate goal of the logical layer of the Semantic Web. To this aim an ad-hoc mark-up language for this layer is currently under discussion. It is intended to follow the tradition of hybrid knowledge representation and reasoning systems such as $\\mathcal{AL}$-log that integrates the description logic $\\mathcal{ALC}$ and the function-free Horn clausal language \\textsc{Datalog}. In this paper we consider the problem of automating the acquisition of the...

  6. Recognizing lexical and semantic change patterns in evolving life science ontologies to inform mapping adaptation.

    Science.gov (United States)

    Dos Reis, Julio Cesar; Dinh, Duy; Da Silveira, Marcos; Pruski, Cédric; Reynaud-Delaître, Chantal

    2015-03-01

    Mappings established between life science ontologies require significant efforts to maintain them up to date due to the size and frequent evolution of these ontologies. In consequence, automatic methods for applying modifications on mappings are highly demanded. The accuracy of such methods relies on the available description about the evolution of ontologies, especially regarding concepts involved in mappings. However, from one ontology version to another, a further understanding of ontology changes relevant for supporting mapping adaptation is typically lacking. This research work defines a set of change patterns at the level of concept attributes, and proposes original methods to automatically recognize instances of these patterns based on the similarity between attributes denoting the evolving concepts. This investigation evaluates the benefits of the proposed methods and the influence of the recognized change patterns to select the strategies for mapping adaptation. The summary of the findings is as follows: (1) the Precision (>60%) and Recall (>35%) achieved by comparing manually identified change patterns with the automatic ones; (2) a set of potential impact of recognized change patterns on the way mappings is adapted. We found that the detected correlations cover ∼66% of the mapping adaptation actions with a positive impact; and (3) the influence of the similarity coefficient calculated between concept attributes on the performance of the recognition algorithms. The experimental evaluations conducted with real life science ontologies showed the effectiveness of our approach to accurately characterize ontology evolution at the level of concept attributes. This investigation confirmed the relevance of the proposed change patterns to support decisions on mapping adaptation. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. OlyMPUS - The Ontology-based Metadata Portal for Unified Semantics

    Science.gov (United States)

    Huffer, E.; Gleason, J. L.

    2015-12-01

    The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS), funded by the NASA Earth Science Technology Office Advanced Information Systems Technology program, is an end-to-end system designed to support data consumers and data providers, enabling the latter to register their data sets and provision them with the semantically rich metadata that drives the Ontology-Driven Interactive Search Environment for Earth Sciences (ODISEES). OlyMPUS leverages the semantics and reasoning capabilities of ODISEES to provide data producers with a semi-automated interface for producing the semantically rich metadata needed to support ODISEES' data discovery and access services. It integrates the ODISEES metadata search system with multiple NASA data delivery tools to enable data consumers to create customized data sets for download to their computers, or for NASA Advanced Supercomputing (NAS) facility registered users, directly to NAS storage resources for access by applications running on NAS supercomputers. A core function of NASA's Earth Science Division is research and analysis that uses the full spectrum of data products available in NASA archives. Scientists need to perform complex analyses that identify correlations and non-obvious relationships across all types of Earth System phenomena. Comprehensive analytics are hindered, however, by the fact that many Earth science data products are disparate and hard to synthesize. Variations in how data are collected, processed, gridded, and stored, create challenges for data interoperability and synthesis, which are exacerbated by the sheer volume of available data. Robust, semantically rich metadata can support tools for data discovery and facilitate machine-to-machine transactions with services such as data subsetting, regridding, and reformatting. Such capabilities are critical to enabling the research activities integral to NASA's strategic plans. However, as metadata requirements increase and competing standards emerge

  8. Building Rules on Top of Ontologies for the Semantic Web with Inductive Logic Programming

    CERN Document Server

    Lisi, Francesca A

    2007-01-01

    Building rules on top of ontologies is the ultimate goal of the logical layer of the Semantic Web. To this aim an ad-hoc mark-up language for this layer is currently under discussion. It is intended to follow the tradition of hybrid knowledge representation and reasoning systems such as $\\mathcal{AL}$-log that integrates the description logic $\\mathcal{ALC}$ and the function-free Horn clausal language \\textsc{Datalog}. In this paper we consider the problem of automating the acquisition of these rules for the Semantic Web. We propose a general framework for rule induction that adopts the methodological apparatus of Inductive Logic Programming and relies on the expressive and deductive power of $\\mathcal{AL}$-log. The framework is valid whatever the scope of induction (description vs. prediction) is. Yet, for illustrative purposes, we also discuss an instantiation of the framework which aims at description and turns out to be useful in Ontology Refinement. Keywords: Inductive Logic Programming, Hybrid Knowledge...

  9. An Ontological Framework for Retrieving Environmental Sounds Using Semantics and Acoustic Content

    Directory of Open Access Journals (Sweden)

    Wichern Gordon

    2010-01-01

    Full Text Available Organizing a database of user-contributed environmental sound recordings allows sound files to be linked not only by the semantic tags and labels applied to them, but also to other sounds with similar acoustic characteristics. Of paramount importance in navigating these databases are the problems of retrieving similar sounds using text- or sound-based queries, and automatically annotating unlabeled sounds. We propose an integrated system, which can be used for text-based retrieval of unlabeled audio, content-based query-by-example, and automatic annotation of unlabeled sound files. To this end, we introduce an ontological framework where sounds are connected to each other based on the similarity between acoustic features specifically adapted to environmental sounds, while semantic tags and sounds are connected through link weights that are optimized based on user-provided tags. Furthermore, tags are linked to each other through a measure of semantic similarity, which allows for efficient incorporation of out-of-vocabulary tags, that is, tags that do not yet exist in the database. Results on two freely available databases of environmental sounds contributed and labeled by nonexpert users demonstrate effective recall, precision, and average precision scores for both the text-based retrieval and annotation tasks.

  10. A Generalized Framework for Ontology-Based Information Retrieval Application to a public-transportation system

    OpenAIRE

    2014-01-01

    In this paper we present a generic framework for ontology-based information retrieval. We focus on the recognition of semantic information extracted from data sources and the mapping of this knowledge into ontology. In order to achieve more scalability, we propose an approach for semantic indexing based on entity retrieval model. In addition, we have used ontology of public transportation domain in order to validate these proposals. Finally, we evaluated our system using ontology mapping and ...

  11. Activity Recognition and Semantic Description for Indoor Mobile Localization

    Science.gov (United States)

    Guo, Sheng; Xiong, Hanjiang; Zheng, Xianwei; Zhou, Yan

    2017-01-01

    As a result of the rapid development of smartphone-based indoor localization technology, location-based services in indoor spaces have become a topic of interest. However, to date, the rich data resulting from indoor localization and navigation applications have not been fully exploited, which is significant for trajectory correction and advanced indoor map information extraction. In this paper, an integrated location acquisition method utilizing activity recognition and semantic information extraction is proposed for indoor mobile localization. The location acquisition method combines pedestrian dead reckoning (PDR), human activity recognition (HAR) and landmarks to acquire accurate indoor localization information. Considering the problem of initial position determination, a hidden Markov model (HMM) is utilized to infer the user’s initial position. To provide an improved service for further applications, the landmarks are further assigned semantic descriptions by detecting the user’s activities. The experiments conducted in this study confirm that a high degree of accuracy for a user’s indoor location can be obtained. Furthermore, the semantic information of a user’s trajectories can be extracted, which is extremely useful for further research into indoor location applications. PMID:28335555

  12. Activity Recognition and Semantic Description for Indoor Mobile Localization.

    Science.gov (United States)

    Guo, Sheng; Xiong, Hanjiang; Zheng, Xianwei; Zhou, Yan

    2017-03-21

    As a result of the rapid development of smartphone-based indoor localization technology, location-based services in indoor spaces have become a topic of interest. However, to date, the rich data resulting from indoor localization and navigation applications have not been fully exploited, which is significant for trajectory correction and advanced indoor map information extraction. In this paper, an integrated location acquisition method utilizing activity recognition and semantic information extraction is proposed for indoor mobile localization. The location acquisition method combines pedestrian dead reckoning (PDR), human activity recognition (HAR) and landmarks to acquire accurate indoor localization information. Considering the problem of initial position determination, a hidden Markov model (HMM) is utilized to infer the user's initial position. To provide an improved service for further applications, the landmarks are further assigned semantic descriptions by detecting the user's activities. The experiments conducted in this study confirm that a high degree of accuracy for a user's indoor location can be obtained. Furthermore, the semantic information of a user's trajectories can be extracted, which is extremely useful for further research into indoor location applications.

  13. Exploring information from the topology beneath the Gene Ontology terms to improve semantic similarity measures.

    Science.gov (United States)

    Zhang, Shu-Bo; Lai, Jian-Huang

    2016-07-15

    Measuring the similarity between pairs of biological entities is important in molecular biology. The introduction of Gene Ontology (GO) provides us with a promising approach to quantifying the semantic similarity between two genes or gene products. This kind of similarity measure is closely associated with the GO terms annotated to biological entities under consideration and the structure of the GO graph. However, previous works in this field mainly focused on the upper part of the graph, and seldom concerned about the lower part. In this study, we aim to explore information from the lower part of the GO graph for better semantic similarity. We proposed a framework to quantify the similarity measure beneath a term pair, which takes into account both the information two ancestral terms share and the probability that they co-occur with their common descendants. The effectiveness of our approach was evaluated against seven typical measurements on public platform CESSM, protein-protein interaction and gene expression datasets. Experimental results consistently show that the similarity derived from the lower part contributes to better semantic similarity measure. The promising features of our approach are the following: (1) it provides a mirror model to characterize the information two ancestral terms share with respect to their common descendant; (2) it quantifies the probability that two terms co-occur with their common descendant in an efficient way; and (3) our framework can effectively capture the similarity measure beneath two terms, which can serve as an add-on to improve traditional semantic similarity measure between two GO terms. The algorithm was implemented in Matlab and is freely available from http://ejl.org.cn/bio/GOBeneath/. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. TopoICSim: a new semantic similarity measure based on gene ontology.

    Science.gov (United States)

    Ehsani, Rezvan; Drabløs, Finn

    2016-07-29

    The Gene Ontology (GO) is a dynamic, controlled vocabulary that describes the cellular function of genes and proteins according to tree major categories: biological process, molecular function and cellular component. It has become widely used in many bioinformatics applications for annotating genes and measuring their semantic similarity, rather than their sequence similarity. Generally speaking, semantic similarity measures involve the GO tree topology, information content of GO terms, or a combination of both. Here we present a new semantic similarity measure called TopoICSim (Topological Information Content Similarity) which uses information on the specific paths between GO terms based on the topology of the GO tree, and the distribution of information content along these paths. The TopoICSim algorithm was evaluated on two human benchmark datasets based on KEGG pathways and Pfam domains grouped as clans, using GO terms from either the biological process or molecular function. The performance of the TopoICSim measure compared favorably to five existing methods. Furthermore, the TopoICSim similarity was also tested on gene/protein sets defined by correlated gene expression, using three human datasets, and showed improved performance compared to two previously published similarity measures. Finally we used an online benchmarking resource which evaluates any similarity measure against a set of 11 similarity measures in three tests, using gene/protein sets based on sequence similarity, Pfam domains, and enzyme classifications. The results for TopoICSim showed improved performance relative to most of the measures included in the benchmarking, and in particular a very robust performance throughout the different tests. The TopoICSim similarity measure provides a competitive method with robust performance for quantification of semantic similarity between genes and proteins based on GO annotations. An R script for TopoICSim is available at http://bigr.medisin.ntnu.no/tools/TopoICSim.R .

  15. A chronic disease dietary consultation system using OWL-based ontologies and semantic rules.

    Science.gov (United States)

    Chi, Yu-Liang; Chen, Tsang-Yao; Tsai, Wan-Ting

    2015-02-01

    Chronic diseases patients often require constant dietary control that involves complicated interaction among factors such as the illness stage, the patient's physical condition, the patient's activity level, the amount of food intake, and key nutrient restrictions. This study aims to integrate multiple knowledge sources for problem solving modeling and knowledge-based system (KBS) development. A chronic kidney disease dietary consultation system is constructed by using Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) to demonstrate how a KBS approach can achieve sound problem solving modeling and effective knowledge inference. For system evaluation, information from 84 case patients is used to evaluate the performance of the system in recommending appropriate food serving amounts from different food groups for balanced key nutrient ingestion. The results show that, excluding interference factors, the OWL-based KBS can achieve accurate problem solving reasoning while maintaining knowledge base shareability and extensibility.

  16. Mining in Ontology with Multi Agent System in Semantic Web : A Novel Approach

    Directory of Open Access Journals (Sweden)

    Vishal Jain1

    2014-10-01

    Full Text Available A large amount of data is present on the web. It contains huge number of web pages and to find suitable information from them is very cumbersome task. There is need to organize data in formal manner so that user can easily access and use them. To retrieve information from documents, there are many Information Retrieval (IR techniques. Current IR techniques are not so advanced that they can be able to exploit semantic knowledge within documents and give precise results. IR technology is major factor responsible for handling annotations in Semantic Web (SW languages. With the rate of growth of web and huge amount of information available on the web which may be in unstructured, semi structured or structured form, it has become increasingly difficult to identify the relevant pieces of information on the internet. IR technology is major factor responsible for handling annotations in Semantic Web (SW languages. Knowledgeable representation languages are used for retrieving information. So, there is need to build an ontology that uses well defined methodology and process of developing ontology is called Ontology Development. Secondly, Cloud computing and data mining have become famous phenomena in the current application of information technology. With the changing trends and emerging of the new concept in the information technology sector, data mining and knowledge discovery have proved to be of significant importance. Data mining can be defined as the process of extracting data or information from a database which is not explicitly defined by the database and can be used to come up with generalized conclusions based on the trends obtained from the data. A database may be described as a collection of formerly structured data. Multi agents data mining may be defined as the use of various agents cooperatively interact with the environment to achieve a specified objective. Multi agents will always act on behalf of users and will coordinate, cooperate

  17. The role of ontologies for sustainable, semantically interoperable and trustworthy EHR solutions.

    Science.gov (United States)

    Blobel, Bernd; Kalra, Dipak; Koehn, Marc; Lunn, Ken; Pharow, Peter; Ruotsalainen, Pekka; Schulz, Stefan; Smith, Barry

    2009-01-01

    As health systems around the world turn towards highly distributed, specialized and cooperative structures to increase quality and safety of care as well as efficiency and efficacy of delivery processes, there is a growing need for supporting communication and collaboration of all parties involved with advanced ICT solutions. The Electronic Health Record (EHR) provides the information platform which is maturing towards the eHealth core application. To meet the requirements for sustainable, semantically interoperable, and trustworthy EHR solutions, different standards and different national strategies have been established. The workshop summarizes the requirements for such advanced EHR systems and their underlying architecture, presents different strategies and solutions advocated by corresponding protagonists, discusses pros and cons as well as harmonization and migration strategies for those approaches. It particularly highlights a turn towards ontology-driven architectures. The workshop is a joint activity of the EFMI Working Groups "Electronic Health Records" and "Security, Safety and Ethics".

  18. The Open-Multinet Upper Ontology Towards the Semantic-based Management of Federated Infrastructures

    Directory of Open Access Journals (Sweden)

    Alexander Willner

    2015-12-01

    Full Text Available The Internet remains an unfinished work. There are several approaches to enhancing it that have been experimentally validated within federated testbed environments. To best gain scientific knowledge from these studies, reproducibility and automation are needed in all areas of the experiment life cycle. Within the GENI and FIRE context, several architectures and protocols have been developed for this purpose. However, a major open research issue remains, namely the description and discovery of the heterogeneous resources involved. To remedy this, we propose a semantic information model that can be used to allow declarative interoperability, build dependency graphs, validate requests, infer knowledge and conduct complex queries. The requirements for such an information model have been extracted from current international Future Internet research projects and the practicality of the model is being evaluated through initial implementations. The main outcome of this work is the definition of the Open-Multinet Upper Ontology and related sub-ontologies, which can be used to describe and manage federated infrastructures and their resources.

  19. An ontology-based semantic configuration approach to constructing Data as a Service for enterprises

    Science.gov (United States)

    Cai, Hongming; Xie, Cheng; Jiang, Lihong; Fang, Lu; Huang, Chenxi

    2016-03-01

    To align business strategies with IT systems, enterprises should rapidly implement new applications based on existing information with complex associations to adapt to the continually changing external business environment. Thus, Data as a Service (DaaS) has become an enabling technology for enterprise through information integration and the configuration of existing distributed enterprise systems and heterogonous data sources. However, business modelling, system configuration and model alignment face challenges at the design and execution stages. To provide a comprehensive solution to facilitate data-centric application design in a highly complex and large-scale situation, a configurable ontology-based service integrated platform (COSIP) is proposed to support business modelling, system configuration and execution management. First, a meta-resource model is constructed and used to describe and encapsulate information resources by way of multi-view business modelling. Then, based on ontologies, three semantic configuration patterns, namely composite resource configuration, business scene configuration and runtime environment configuration, are designed to systematically connect business goals with executable applications. Finally, a software architecture based on model-view-controller (MVC) is provided and used to assemble components for software implementation. The result of the case study demonstrates that the proposed approach provides a flexible method of implementing data-centric applications.

  20. Measuring semantic similarities by combining gene ontology annotations and gene co-function networks.

    Science.gov (United States)

    Peng, Jiajie; Uygun, Sahra; Kim, Taehyong; Wang, Yadong; Rhee, Seung Y; Chen, Jin

    2015-02-14

    Gene Ontology (GO) has been used widely to study functional relationships between genes. The current semantic similarity measures rely only on GO annotations and GO structure. This limits the power of GO-based similarity because of the limited proportion of genes that are annotated to GO in most organisms. We introduce a novel approach called NETSIM (network-based similarity measure) that incorporates information from gene co-function networks in addition to using the GO structure and annotations. Using metabolic reaction maps of yeast, Arabidopsis, and human, we demonstrate that NETSIM can improve the accuracy of GO term similarities. We also demonstrate that NETSIM works well even for genomes with sparser gene annotation data. We applied NETSIM on large Arabidopsis gene families such as cytochrome P450 monooxygenases to group the members functionally and show that this grouping could facilitate functional characterization of genes in these families. Using NETSIM as an example, we demonstrated that the performance of a semantic similarity measure could be significantly improved after incorporating genome-specific information. NETSIM incorporates both GO annotations and gene co-function network data as a priori knowledge in the model. Therefore, functional similarities of GO terms that are not explicitly encoded in GO but are relevant in a taxon-specific manner become measurable when GO annotations are limited. Supplementary information and software are available at http://www.msu.edu/~jinchen/NETSIM .

  1. 本体语义检索系统%A semantic retrieval system based on ontology

    Institute of Scientific and Technical Information of China (English)

    王璐; 于超; 王博; 王国春; 林金花; 李辉

    2013-01-01

    基于关键词匹配的检索方法存在不足,使用分布式大数据处理技术,基于本体对用户输入的查询关键词进行查询扩展,利用L ucene针对扩展后的关键词进行检索,按照语义相似度将检索结果排序后返回给用户。实验表明,基于本体的语义检索系统在查全率和查准率两个方面均优于传统检索方法。%Traditional retrieval method based on keyword matching does not work efficiently in some aspects .With the distributed bulk data processing technology , the user input query keywords is extended based on ontology and the extended keywords are retrieved by means of Lucene . The retrieved results are sequenced according to the semantic similarity and then backed to the users .The experiments show that the semantic retrieval system is better than the traditional one on both the precision ratio and recall ratio .

  2. Semantic layer based ontologies to reformulate the neurological queries in mobile environment

    Directory of Open Access Journals (Sweden)

    Youssouf El Allioui

    2010-09-01

    Full Text Available A crucial requirement for the context-aware service provisioning is the dynamic retrieval and interaction with local resources, i.e., resource discovery. The high degree of dynamicity and heterogeneity of mobile environments requires to rethink and/or extend traditional discovery solutions to support more intelligent service search and retrieval, personalized to user context conditions. Several research efforts have recently emerged in the field of service discovery that, based on semantic data representation and technologies, allow flexible matching between user requirements and service capabilities in open and dynamic deployment scenarios. Our research work aims at providing suitable answering mechanisms of mobile requests by taking into account user contexts (preferences, profiles, physical location, temporal information. This paper proposes an ontology, culled O'Neurolog, to capture semantic knowledge a valuable in Neurology domain in order to assist users (doctor, patient, administration when querying Neurology knowledge bases in mobile environment. The increasing diffusion of portable devices with wireless connectivity enables new pervasive scenarios, where users require tailored service access according to their needs, position, and execution/environment conditions.

  3. Recognition rights, mental health consumers and reconstructive cultural semantics

    Directory of Open Access Journals (Sweden)

    Radden Jennifer H

    2012-01-01

    Full Text Available Abstract Introduction Those in mental health-related consumer movements have made clear their demands for humane treatment and basic civil rights, an end to stigma and discrimination, and a chance to participate in their own recovery. But theorizing about the politics of recognition, 'recognition rights' and epistemic justice, suggests that they also have a stake in the broad cultural meanings associated with conceptions of mental health and illness. Results First person accounts of psychiatric diagnosis and mental health care (shown here to represent 'counter stories' to the powerful 'master narrative' of biomedical psychiatry, offer indications about how experiences of mental disorder might be reframed and redefined as part of efforts to acknowledge and honor recognition rights and epistemic justice. However, the task of cultural semantics is one for the entire culture, not merely consumers. These new meanings must be negotiated. When they are not the result of negotiation, group-wrought definitions risk imposing a revision no less constraining than the mis-recognizing one it aims to replace. Contested realities make this a challenging task when it comes to cultural meanings about mental disorder. Examples from mental illness memoirs about two contested realities related to psychosis are examined here: the meaninglessness of symptoms, and the role of insight into illness. They show the magnitude of the challenge involved - for consumers, practitioners, and the general public - in the reconstruction of these new meanings and realities. Conclusion To honor recognition rights and epistemic justice acknowledgement must be made of the heterogeneity of the effects of, and of responses to, psychiatric diagnosis and care, and the extent of the challenge of the reconstructive cultural semantics involved.

  4. Ontology-based Information Retrieval

    DEFF Research Database (Denmark)

    Styltsvig, Henrik Bulskov

    of concept similarity in query evaluation is discussed. A semantic expansion approach that incorporates concept similarity is introduced and a generalized fuzzy set retrieval model that applies expansion during query evaluation is presented. While not commonly used in present information retrieval systems......In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information...... retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use...

  5. Desain Sistem Semantic Data Warehouse dengan Metode Ontology dan Rule Based untuk Mengolah Data Akademik Universitas XYZ di Bali

    Directory of Open Access Journals (Sweden)

    Made Pradnyana Ambara

    2016-06-01

    Full Text Available Data warehouse pada umumnya yang sering dikenal data warehouse tradisional mempunyai beberapa kelemahan yang mengakibatkan kualitas data yang dihasilkan tidak spesifik dan efektif. Sistem semantic data warehouse merupakan solusi untuk menangani permasalahan pada data warehouse tradisional dengan kelebihan antara lain: manajeman kualitas data yang spesifik dengan format data seragam untuk mendukung laporan OLAP yang baik, dan performance pencarian informasi yang lebih efektif dengan kata kunci bahasa alami. Pemodelan sistem semantic data warehouse menggunakan metode ontology menghasilkan model resource description framework schema (RDFS logic yang akan ditransformasikan menjadi snowflake schema. Laporan akademik yang dibutuhkan dihasilkan melalui metode nine step Kimball dan pencarian semantic menggunakan metode rule based. Pengujian dilakukan menggunakan dua metode uji yaitu pengujian dengan black box testing dan angket kuesioner cheklist. Dari hasil penelitian ini dapat disimpulkan bahwa sistem semantic data warehouse dapat membantu proses pengolahan data akademik yang menghasilkan laporan yang berkualitas untuk mendukung proses pengambilan keputusan.

  6. A Case Study of Semantic Annotation with Multi - Ontology by Upper- level Ontology Unitive Control%顶级本体统控的多本体语义标注实证研究

    Institute of Scientific and Technical Information of China (English)

    米杨; 曹锦丹

    2012-01-01

    The paper takes upper - level Ontology as the core technology, integrates domain Ontologies by upper - level Ontology unitive control, and annotates information semantically by integration Ontology with tools like Prot6g6 and GATE for empirical research. It integrates the Nasal Inflammation Disease Ontology and National Essential Drugs Ontology as one Ontology to annotate the Electronic Medical Record information resources, and the semantic annotation library can be saved as XML format. This research provides empirical evidence for semantic annotation schema with integration Ontology using upper- level Ontology unitive control, and the annotated resources can match the Ontology element in semantic re- trieval so as to realize the semantic applications like knowledge discovery.%以顶级本体作为本体工程的技术核心,通过顶级本体统控领域本体整合、整合本体语义标注等手段,利用Prot6g6、GATE等工具整合中文鼻部炎症疾病知识本体和国家基本药物知识本体,实现以整合本体标注电子病历信息资源,并保存为XML形式语义标注库。本研究实证顶级本体统控的整合本体语义标注模式,标注后的资源叮在语义检索阶段匹配本体元素,进而实现知识发现等语义应用。

  7. A Concept Lattice for Semantic Integration of Geo-Ontologies Based on Weight of Inclusion Degree Importance and Information Entropy

    Directory of Open Access Journals (Sweden)

    Jia Xiao

    2016-11-01

    Full Text Available Constructing a merged concept lattice with formal concept analysis (FCA is an important research direction in the field of integrating multi-source geo-ontologies. Extracting essential geographical properties and reducing the concept lattice are two key points of previous research. A formal integration method is proposed to address the challenges in these two areas. We first extract essential properties from multi-source geo-ontologies and use FCA to build a merged formal context. Second, the combined importance weight of each single attribute of the formal context is calculated by introducing the inclusion degree importance from rough set theory and information entropy; then a weighted formal context is built from the merged formal context. Third, a combined weighted concept lattice is established from the weighted formal context with FCA and the importance weight value of every concept is defined as the sum of weight of attributes belonging to the concept’s intent. Finally, semantic granularity of concept is defined by its importance weight; we, then gradually reduce the weighted concept lattice by setting up diminishing threshold of semantic granularity. Additionally, all of those reduced lattices are organized into a regular hierarchy structure based on the threshold of semantic granularity. A workflow is designed to demonstrate this procedure. A case study is conducted to show feasibility and validity of this method and the procedure to integrate multi-source geo-ontologies.

  8. A case-study of ontology-driven semantic mediation of flower-visiting data from heterogeneous data-stores in three South African natural history collections

    CSIR Research Space (South Africa)

    Coetzer, W

    2013-05-01

    Full Text Available -1 First International Workshop on Semantics for Biodiversity, Montpellier, France, 26-27 May 2013 A Case-Study of Ontology-Driven Semantic Mediation of Flower-Visiting Data from Heterogeneous Data-Stores in Three South African Natural History...

  9. Dialog-Based 3D-Image Recognition Using a Domain Ontology

    Science.gov (United States)

    Hois, Joana; Wünstel, Michael; Bateman, John A.; Röfer, Thomas

    The combination of vision and speech, together with the resulting necessity for formal representations, builds a central component of an autonomous system. A robot that is supposed to navigate autonomously through space must be able to perceive its environment as automatically as possible. But each recognition system has its own inherent limits. Especially a robot whose task is to navigate through unknown terrain has to deal with unidentified or even unknown objects, thus compounding the recognition problem still further. The system described in this paper takes this into account by trying to identify objects based on their functionality where possible. To handle cases where recognition is insufficient, we examine here two further strategies: on the one hand, the linguistic reference and labeling of the unidentified objects and, on the other hand, ontological deduction. This approach then connects the probabilistic area of object recognition with the logical area of formal reasoning. In order to support formal reasoning, additional relational scene information has to be supplied by the recognition system. Moreover, for a sound ontological basis for these reasoning tasks, it is necessary to define a domain ontology that provides for the representation of real-world objects and their corresponding spatial relations in linguistic and physical respects. Physical spatial relations and objects are measured by the visual system, whereas linguistic spatial relations and objects are required for interactions with a user.

  10. The IRI/LDEO Climate Data Library Ontology: placing climate data on the Semantic Web

    Science.gov (United States)

    Blumenthal, M. B.; del Corral, J.; Grover-Kopec, E.; Bell, M.

    2005-12-01

    The standards underlying the Semantic Web -- Resource Description Framework (RDF) and Web Ontology Language (OWL) -- show great promise in addressing some of the basic problems in earth science metadata. They provide a framework for explicitly describing the data models implicit in programs that display and manipulate data. They also provide a framework where multiple metadata standards can be described. Most importantly, these data models and metadata standards can be interrelated, a key step in creating interoperability. As a exercise in understanding how this framework might be used, we have created an RDF expression of the datasets and some of the metadata in the Climate Data Library. This includes concepts like datasets, units, dependent variables, and independent variables. We have also created an RDF expression of a taxonomy that could form the basis of a earth data search interface. These concepts include location, time, author, and institution. A series of inference engines are then used to infer the connections between data-oriented concepts of the data library to the distinctly different concepts of the data search.

  11. Generating Application Ontologies from Reference Ontologies

    OpenAIRE

    Shaw, Marianne; Detwiler, Landon T.; Brinkley, James F.; Suciu, Dan

    2008-01-01

    The semantic web provides the possiblity of linking together large numbers of biomedical ontologies. Unfortunately, many of the biomedical ontologies that have been developed are domain-specific and do not share a common structure that will allow them to be easily combined. Reference ontologies provide the necessary ontological framework for linking together these smaller, specialized ontologies.

  12. Word recognition in Alzheimer's disease: Effects of semantic degeneration.

    Science.gov (United States)

    Cuetos, Fernando; Arce, Noemí; Martínez, Carmen; Ellis, Andrew W

    2017-03-01

    Impairments of word recognition in Alzheimer's disease (AD) have been less widely investigated than impairments affecting word retrieval and production. In particular, we know little about what makes individual words easier or harder for patients with AD to recognize. We used a lexical selection task in which participants were shown sets of four items, each set consisting of one word and three non-words. The task was simply to point to the word on each trial. Forty patients with mild-to-moderate AD were significantly impaired on this task relative to matched controls who made very few errors. The number of patients with AD able to recognize each word correctly was predicted by the frequency, age of acquisition, and imageability of the words, but not by their length or number of orthographic neighbours. Patient Mini-Mental State Examination and phonological fluency scores also predicted the number of words recognized. We propose that progressive degradation of central semantic representations in AD differentially affects the ability to recognize low-imageability, low-frequency, late-acquired words, with the same factors affecting word recognition as affecting word retrieval. © 2015 The British Psychological Society.

  13. An ontology-based measure to compute semantic similarity in biomedicine

    National Research Council Canada - National Science Library

    Batet, Montserrat; Sánchez, David; Valls, Aida

    ... (ontologies, thesauri, domain corpora, etc.) have been proposed. Some of these measures have been adapted to the biomedical field by incorporating domain information extracted from clinical data or from medical ontologies...

  14. Ontology Design Patterns: Bridging the Gap Between Local Semantic Use Cases and Large-Scale, Long-Term Data Integration

    Science.gov (United States)

    Shepherd, Adam; Arko, Robert; Krisnadhi, Adila; Hitzler, Pascal; Janowicz, Krzysztof; Chandler, Cyndy; Narock, Tom; Cheatham, Michelle; Schildhauer, Mark; Jones, Matt; Raymond, Lisa; Mickle, Audrey; Finin, Tim; Fils, Doug; Carbotte, Suzanne; Lehnert, Kerstin

    2015-04-01

    Integrating datasets for new use cases is one of the common drivers for adopting semantic web technologies. Even though linked data principles enables this type of activity over time, the task of reconciling new ontological commitments for newer use cases can be daunting. This situation was faced by the Biological and Chemical Oceanography Data Management Office (BCO-DMO) as it sought to integrate its existing linked data with other data repositories to address newer scientific use cases as a partner in the GeoLink Project. To achieve a successful integration with other GeoLink partners, BCO-DMO's metadata would need to be described using the new ontologies developed by the GeoLink partners - a situation that could impact semantic inferencing, pre-existing software and external users of BCO-DMO's linked data. This presentation describes the process of how GeoLink is bridging the gap between local, pre-existing ontologies to achieve scientific metadata integration for all its partners through the use of ontology design patterns. GeoLink, an NSF EarthCube Building Block, brings together experts from the geosciences, computer science, and library science in an effort to improve discovery and reuse of data and knowledge. Its participating repositories include content from field expeditions, laboratory analyses, journal publications, conference presentations, theses/reports, and funding awards that span scientific studies from marine geology to marine ecology and biogeochemistry to paleoclimatology. GeoLink's outcomes include a set of reusable ontology design patterns (ODPs) that describe core geoscience concepts, a network of Linked Data published by participating repositories using those ODPs, and tools to facilitate discovery of related content in multiple repositories.

  15. Effects of Semantic Context and Fundamental Frequency Contours on Mandarin Speech Recognition by Second Language Learners.

    Science.gov (United States)

    Zhang, Linjun; Li, Yu; Wu, Han; Li, Xin; Shu, Hua; Zhang, Yang; Li, Ping

    2016-01-01

    Speech recognition by second language (L2) learners in optimal and suboptimal conditions has been examined extensively with English as the target language in most previous studies. This study extended existing experimental protocols (Wang et al., 2013) to investigate Mandarin speech recognition by Japanese learners of Mandarin at two different levels (elementary vs. intermediate) of proficiency. The overall results showed that in addition to L2 proficiency, semantic context, F0 contours, and listening condition all affected the recognition performance on the Mandarin sentences. However, the effects of semantic context and F0 contours on L2 speech recognition diverged to some extent. Specifically, there was significant modulation effect of listening condition on semantic context, indicating that L2 learners made use of semantic context less efficiently in the interfering background than in quiet. In contrast, no significant modulation effect of listening condition on F0 contours was found. Furthermore, there was significant interaction between semantic context and F0 contours, indicating that semantic context becomes more important for L2 speech recognition when F0 information is degraded. None of these effects were found to be modulated by L2 proficiency. The discrepancy in the effects of semantic context and F0 contours on L2 speech recognition in the interfering background might be related to differences in processing capacities required by the two types of information in adverse listening conditions.

  16. Effects of Semantic Context and Fundamental Frequency Contours on Mandarin Speech Recognition by Second Language Learners

    Science.gov (United States)

    Zhang, Linjun; Li, Yu; Wu, Han; Li, Xin; Shu, Hua; Zhang, Yang; Li, Ping

    2016-01-01

    Speech recognition by second language (L2) learners in optimal and suboptimal conditions has been examined extensively with English as the target language in most previous studies. This study extended existing experimental protocols (Wang et al., 2013) to investigate Mandarin speech recognition by Japanese learners of Mandarin at two different levels (elementary vs. intermediate) of proficiency. The overall results showed that in addition to L2 proficiency, semantic context, F0 contours, and listening condition all affected the recognition performance on the Mandarin sentences. However, the effects of semantic context and F0 contours on L2 speech recognition diverged to some extent. Specifically, there was significant modulation effect of listening condition on semantic context, indicating that L2 learners made use of semantic context less efficiently in the interfering background than in quiet. In contrast, no significant modulation effect of listening condition on F0 contours was found. Furthermore, there was significant interaction between semantic context and F0 contours, indicating that semantic context becomes more important for L2 speech recognition when F0 information is degraded. None of these effects were found to be modulated by L2 proficiency. The discrepancy in the effects of semantic context and F0 contours on L2 speech recognition in the interfering background might be related to differences in processing capacities required by the two types of information in adverse listening conditions. PMID:27378997

  17. GOssTo: a stand-alone application and a web tool for calculating semantic similarities on the Gene Ontology.

    Science.gov (United States)

    Caniza, Horacio; Romero, Alfonso E; Heron, Samuel; Yang, Haixuan; Devoto, Alessandra; Frasca, Marco; Mesiti, Marco; Valentini, Giorgio; Paccanaro, Alberto

    2014-08-01

    We present GOssTo, the Gene Ontology semantic similarity Tool, a user-friendly software system for calculating semantic similarities between gene products according to the Gene Ontology. GOssTo is bundled with six semantic similarity measures, including both term- and graph-based measures, and has extension capabilities to allow the user to add new similarities. Importantly, for any measure, GOssTo can also calculate the Random Walk Contribution that has been shown to greatly improve the accuracy of similarity measures. GOssTo is very fast, easy to use, and it allows the calculation of similarities on a genomic scale in a few minutes on a regular desktop machine. alberto@cs.rhul.ac.uk GOssTo is available both as a stand-alone application running on GNU/Linux, Windows and MacOS from www.paccanarolab.org/gossto and as a web application from www.paccanarolab.org/gosstoweb. The stand-alone application features a simple and concise command line interface for easy integration into high-throughput data processing pipelines. © The Author 2014. Published by Oxford University Press.

  18. Intrusion Correlation Using Ontologies and Multi-agent Systems

    Science.gov (United States)

    Isaza, Gustavo; Castillo, Andrés; López, Marcelo; Castillo, Luis; López, Manuel

    This paper proposes an ontology model for representing intrusion detection events and prevention rules, integrating multiagent systems based on unsupervised and supervised techniques for classification, correlation and pattern recognition. The semantic model describes attacks signatures, reaction tasks, axioms with alerts communication and correlation; nevertheless we have developed the prevention architecture integrated with another security tools. This article focuses on the approach to incorporate semantic operations that facilitate alerts correlation process and providing the inference and reasoning to the ontology model.

  19. The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

    Science.gov (United States)

    Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; Vasilevsky, Nicole; Baynam, Gareth; Zemojtel, Tomasz; Schriml, Lynn Marie; Kibbe, Warren Alden; Schofield, Paul N.; Beck, Tim; Vasant, Drashtti; Brookes, Anthony J.; Zankl, Andreas; Washington, Nicole L.; Mungall, Christopher J.; Lewis, Suzanna E.; Haendel, Melissa A.; Parkinson, Helen; Robinson, Peter N.

    2015-01-01

    The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available. PMID:26119816

  20. SPASE "allowed values" ontology - Semantic Web based glue for the connection of EU-ESPAS and Japanese IUGONET projects

    Science.gov (United States)

    Ritschel, B.; Neher, G.; Borchert, F.

    2012-12-01

    Both the European Union project ESPAS (2011-2015) and the Japanese IUGONET project (2009-2014) have the same scientific objects: the design, implementation, and provision of an e-science infrastructure for the retrieval and access to space weather relevant data, information and value added services. Despite similarity of the data model, basic system ideas, and techniques the physical implementation of the system backend and web portal are different. The IUGONET system, which is already operating since 2011, is based on DSPACE's metadata registering, retrieving, providing and harvesting capabilities, whereas the ESPAS system software (still in development) is based on OGC compatible standards and components. IUGONET uses an extension of the SPASE data model, both for the structure and for the values of metadata. ESPAS plans to use an enhanced version of the SPASE based context related values. This means, from a semantic point of view, the used keyword vocabulary for the description of context information of information objects, such as e.g. data files, is almost the same in both projects. Modeling the controlled SPASE keyword vocabulary ("allowed values") in the SPASE standard as SKOS based ontology enables the use and reuse of a common and standardized keyword vocabulary in the space weather domain. This vocabulary can be reused in related projects like the GFZ ISDC ontology network that uses a semantic web based approach and related implications such as linked data integration and inference based reasoning. This paper describes a first modeling approach of the SPASE keyword ontology based on SPASE version 2.2.2 and the connection with other keyword vocabularies. Another aspect is the demonstration of the integration of the SPASE keyword ontology into the SPACE software and the description of the planned integration into the ESPAS software.

  1. Combining Semantic and Acoustic Features for Valence and Arousal Recognition in Speech

    DEFF Research Database (Denmark)

    Karadogan, Seliz; Larsen, Jan

    2012-01-01

    The recognition of affect in speech has attracted a lot of interest recently; especially in the area of cognitive and computer sciences. Most of the previous studies focused on the recognition of basic emotions (such as happiness, sadness and anger) using categorical approach. Recently, the focus...... has been shifting towards dimensional affect recognition based on the idea that emotional states are not independent from one another but related in a systematic manner. In this paper, we design a continuous dimensional speech affect recognition model that combines acoustic and semantic features. We...... show that combining semantic and acoustic information for dimensional speech recognition improves the results. Moreover, we show that valence is better estimated using semantic features while arousal is better estimated using acoustic features....

  2. [Key effect genes responding to nerve injury identified by gene ontology and computer pattern recognition].

    Science.gov (United States)

    Pan, Qian; Peng, Jin; Zhou, Xue; Yang, Hao; Zhang, Wei

    2012-07-01

    In order to screen out important genes from large gene data of gene microarray after nerve injury, we combine gene ontology (GO) method and computer pattern recognition technology to find key genes responding to nerve injury, and then verify one of these screened-out genes. Data mining and gene ontology analysis of gene chip data GSE26350 was carried out through MATLAB software. Cd44 was selected from screened-out key gene molecular spectrum by comparing genes' different GO terms and positions on score map of principal component. Function interferences were employed to influence the normal binding of Cd44 and one of its ligands, chondroitin sulfate C (CSC), to observe neurite extension. Gene ontology analysis showed that the first genes on score map (marked by red *) mainly distributed in molecular transducer activity, receptor activity, protein binding et al molecular function GO terms. Cd44 is one of six effector protein genes, and attracted us with its function diversity. After adding different reagents into the medium to interfere the normal binding of CSC and Cd44, varying-degree remissions of CSC's inhibition on neurite extension were observed. CSC can inhibit neurite extension through binding Cd44 on the neuron membrane. This verifies that important genes in given physiological processes can be identified by gene ontology analysis of gene chip data.

  3. An Ontological Approach to Developing Information Operations Applications for Use on the Semantic Web

    Science.gov (United States)

    2008-09-01

    Advisor Peter Denning Chairman, Department of Computer Science Dan Boger Chairman, Information Sciences Department iv THIS PAGE...Class......................................................................65 Figure 25. DL Expressivity...standard ontology language OWL DL , and proposes a reasoning architecture for these two ontology languages. The key features of the author’s

  4. Gene Ontology synonym generation rules lead to increased performance in biomedical concept recognition.

    Science.gov (United States)

    Funk, Christopher S; Cohen, K Bretonnel; Hunter, Lawrence E; Verspoor, Karin M

    2016-09-09

    Gene Ontology (GO) terms represent the standard for annotation and representation of molecular functions, biological processes and cellular compartments, but a large gap exists between the way concepts are represented in the ontology and how they are expressed in natural language text. The construction of highly specific GO terms is formulaic, consisting of parts and pieces from more simple terms. We present two different types of manually generated rules to help capture the variation of how GO terms can appear in natural language text. The first set of rules takes into account the compositional nature of GO and recursively decomposes the terms into their smallest constituent parts. The second set of rules generates derivational variations of these smaller terms and compositionally combines all generated variants to form the original term. By applying both types of rules, new synonyms are generated for two-thirds of all GO terms and an increase in F-measure performance for recognition of GO on the CRAFT corpus from 0.498 to 0.636 is observed. Additionally, we evaluated the combination of both types of rules over one million full text documents from Elsevier; manual validation and error analysis show we are able to recognize GO concepts with reasonable accuracy (88 %) based on random sampling of annotations. In this work we present a set of simple synonym generation rules that utilize the highly compositional and formulaic nature of the Gene Ontology concepts. We illustrate how the generated synonyms aid in improving recognition of GO concepts on two different biomedical corpora. We discuss other applications of our rules for GO ontology quality assurance, explore the issue of overgeneration, and provide examples of how similar methodologies could be applied to other biomedical terminologies. Additionally, we provide all generated synonyms for use by the text-mining community.

  5. 领域本体中概念间语义相关度的概率估计%Probability estimation for semantic association on domain ontology

    Institute of Scientific and Technical Information of China (English)

    田萱; 李冬梅

    2011-01-01

    A probability model based on Bayesian principles is given to measure the semantic association from a concept to its direct-related concept in domain ontology.The model is based on different semantic relationships,and is estimated according to maximum likelihood estimation. Semantic distance is used to estimate semantic relationships in estimating period.Based on the proposed model,a method to measure semantic association of any two concepts in ontology is given.Experiment results of semantic retrieval on open data show that semantic query expansion performs better than classic semantic query expansion.%根据贝叶斯定理提出一种衡量领域本体中概念间语义相关度的概率模型.该模型定义在不同语义关系之上,基于极大似然估计法利用语义距离来对语义关系进行参数估计.并在此基础给出一种计算任意两个概念之间语义相关度的方法.公开数据集上的实验结果表明该方法估计出的概念语义相关度具有相当的有效性,应用在语义查询扩展中可明显提高检索效果.

  6. Folksonomy中的语义关系呈现:Folksonomy局部本体%Semantic Relations Appearance in Folksonomy: Folksonomy Local Ontology

    Institute of Scientific and Technical Information of China (English)

    张云中

    2012-01-01

    In allusion to the problems of semantic relations appearance in folksonomy, the semantic architecture is reconstructed in the ternary perspective of "users-tags-resources", and the main categories of folksonomy semantic relations is sorted out, then a scientific mapping mechanism from folksonomy semantics to ontology semantics is established, finally a new concept called ' folksonomy local ontology' is proposed and the author gets a conclusion that folksonomy local ontology is the way of folksonomy semantic relations ap- pearance.%针对当前folksonomy语义关系呈现问题,在“用户-标签-资源”的三元视角下重构folksonomy语义体系,理清folksonomy语义关系的主要类别,进而建立科学的folksonomy语义与本体语义的映射机制,最终提出folksonomy局部本体的新概念,指出folksonomy局部本体是folksonomy语义关系呈现的途径。

  7. Capturing Semantic Meaning on User Interface Presence By Creating Its Ontology

    Directory of Open Access Journals (Sweden)

    Elviawaty Muisa Zamzami

    2012-07-01

    Full Text Available Screenshots, known for years as capturing Graphical User Interface by means of print screen button or capturing software, is not only beneficial for creating user guide or user manual document, but also for reverse engineering process. This paper presents a new way of capturing the data appear on a screen by creating the ontology of its interface. Data capturing based on the interaction style of interface or windowing system, known as WIMP (Window Icon Menu Pointer. The Ontology model used as template, called as WIMP-UI. OWL is used as ontology language, Portg as editor tools, and Pellet reasoner for reasoning.

  8. A Semantic Learning Object (SLOWeb-Editor based on Web Ontology Language (OWL using a New OWL2XSLO Approach

    Directory of Open Access Journals (Sweden)

    Zouhair Rimale

    2016-12-01

    Full Text Available Today, we see a strong demand for real-time information, with a rapid growth of m-learning. We also see that there are many educational resources on the Internet. Learning objects (LOs are designed as a means of reusing these resources. Most of these LOs are built for e-learning systems based on desktop computers, which prevents their use on mobile devices. A LO is an area that is open to research and has a lot of potential in the creation, adaptation and production of learning content. There are standards that describe LOs in general as IEEE LOM, SCORM. Semantic web and its associated technologies are increasingly used in electronic document editing while separating the content from the presentation. Creating a LO with the semantic web is complex and raises difficulties because of the editing tools that require general knowledge of XML syntax and related technologies. In this paper, the authors propose a new OWL2XSLO approach based on ontologies (OWL allowing the generation of XML-Schemas LOs. They then derive a semantic LO web editor based on OWL2XSLO approach for the generation of a content type enabling the editing of interactive LOs with XML technology and which can then be integrated into LMS and adapted to the mobile display.

  9. 基于本体的农业数据语义关联发现技术%Ontology based semantic relevant discovery in agriculture data

    Institute of Scientific and Technical Information of China (English)

    徐晓文; 陈维斌; 李海波

    2012-01-01

    提出了基于本体的语义关联发现模型,通过解析构建的农业领域本体,从本体语义路径的深度广度方面计算概念间相关度,并将计算的结果扩充语义知识库。在农业领域模型中关联发现算法的应用与传统的方法相比。结果更符合领域相关性。依据关联发现模型设计了一个茶叶语义检索系统,实验验证了该提出的模型的实用性和可行性。%This paper proposes the ontology based semantic relevant discovery model to solve these problems. By parsing the constructed agriculture domain ontology, we calculate the correlations from the semantic distance of the depth and breadth in ontology, it improves the semantic knowledge base. Compared with the traditional methods, the experimental data in agricultural sector shows that the novel model better corresponded with domain reality. We develop an ontology based tea semantic retrieval system in agriculture on the basis of this model. The realization of the system verifies the feasibility and practicability of the relevant discovery model.

  10. The Effects of Semantic Mapping, Thematic Clustering, and Notebook Keeping on L2 Vocabulary Recognition and Production

    Science.gov (United States)

    Zarei, Abbas Ali; Adami, Saba

    2013-01-01

    To investigate the effects of semantic mapping, thematic clustering, and notebook keeping on L2 vocabulary recognition and production, four groups of intermediate level learners in an EFL institute in Zanjan, Iran participated in the study. Three experimental groups consisted of semantic mapping, semantic feature analysis, and vocabulary notebook…

  11. A TMS examination of semantic radical combinability effects in Chinese character recognition.

    Science.gov (United States)

    Hsiao, Janet Hui-Wen; Shillcock, Richard; Lavidor, Michal

    2006-03-17

    The proposal of human foveal splitting assumes a vertical meridian split in the foveal representation and the consequent contralateral projection of information in the two hemifields to the two hemispheres and has been shown to have important implications for visual word recognition. According to this assumption, in Chinese character recognition, the two halves of a centrally fixated character may be initially projected to and processed in different hemispheres. Here, we describe a repetitive transcranial magnetic stimulation (rTMS) investigation of hemispheric processing in Chinese character recognition, through examining semantic radical combinability effects in a character semantic judgment task. The materials used were a dominant type of Chinese character which consists of a semantic radical on the left and a phonetic radical on the right. Thus, according to the split fovea assumption, the semantic and phonetic radicals are initially projected to and processed in the right hemisphere and the left hemisphere, respectively. We show that rTMS over the left occipital cortex impaired the facilitation of semantic radicals with large combinability, whereas right occipital rTMS did not. This interaction between stimulation site and radical combinability reveals a flexible division of labor between the hemispheres in Chinese character recognition, with each hemisphere responding optimally to the information in the contralateral visual hemifield to which it has direct access. The results are also consistent with the split fovea claim, suggesting functional foveal splitting as a universal processing constraint in reading.

  12. Neural mechanisms of semantic interference and false recognition in short-term memory.

    Science.gov (United States)

    Atkins, Alexandra S; Reuter-Lorenz, Patricia A

    2011-06-01

    Decades of research using the Deese-Roediger-McDermott (DRM) paradigm have demonstrated that episodic memory is vulnerable to semantic distortion, and neuroimaging investigations of this phenomenon have shown dissociations between the neural mechanisms subserving true and false retrieval from long-term memory. Recently, false short-term memories have also been demonstrated, with false recognition of items related in meaning to memoranda encoded less than 5s earlier. Semantic interference is also evident in short-term memory, such that correct rejection of related lures is slowed relative to correct rejection of unrelated lures. The present research constitutes the first fMRI investigation of false recognition and semantic interference in short-term memory using a short-term DRM paradigm in which participants retained 4 semantic associates over a short 4-s filled retention interval. Results showed increased activation in the left mid-ventrolateral prefrontal cortex (BA45) associated with semantic interference, and significant correlations between these increases and behavioral measures of interference across subjects. Furthermore, increases in dorsolateral PFC occurred when related lures were correctly rejected versus falsely remembered. Compared with false recognition, true recognition was associated with increases in left fusiform gyrus, a finding consistent with the notion that increased perceptual processing may distinguish true from false recognition over both short and long retention intervals. Findings are discussed in relation to current models of interference resolution in short-term memory, and suggest that false short-term recognition occurs as a consequence of the failure of frontally mediated cognitive control processes which adjudicate semantic familiarity in support of accurate mnemonic retrieval.

  13. OmniSearch: a semantic search system based on the Ontology for MIcroRNA Target (OMIT) for microRNA-target gene interaction data.

    Science.gov (United States)

    Huang, Jingshan; Gutierrez, Fernando; Strachan, Harrison J; Dou, Dejing; Huang, Weili; Smith, Barry; Blake, Judith A; Eilbeck, Karen; Natale, Darren A; Lin, Yu; Wu, Bin; Silva, Nisansa de; Wang, Xiaowei; Liu, Zixing; Borchert, Glen M; Tan, Ming; Ruttenberg, Alan

    2016-01-01

    As a special class of non-coding RNAs (ncRNAs), microRNAs (miRNAs) perform important roles in numerous biological and pathological processes. The realization of miRNA functions depends largely on how miRNAs regulate specific target genes. It is therefore critical to identify, analyze, and cross-reference miRNA-target interactions to better explore and delineate miRNA functions. Semantic technologies can help in this regard. We previously developed a miRNA domain-specific application ontology, Ontology for MIcroRNA Target (OMIT), whose goal was to serve as a foundation for semantic annotation, data integration, and semantic search in the miRNA field. In this paper we describe our continuing effort to develop the OMIT, and demonstrate its use within a semantic search system, OmniSearch, designed to facilitate knowledge capture of miRNA-target interaction data. Important changes in the current version OMIT are summarized as: (1) following a modularized ontology design (with 2559 terms imported from the NCRO ontology); (2) encoding all 1884 human miRNAs (vs. 300 in previous versions); and (3) setting up a GitHub project site along with an issue tracker for more effective community collaboration on the ontology development. The OMIT ontology is free and open to all users, accessible at: http://purl.obolibrary.org/obo/omit.owl. The OmniSearch system is also free and open to all users, accessible at: http://omnisearch.soc.southalabama.edu/index.php/Software.

  14. Scientific Reproducibility in Biomedical Research: Provenance Metadata Ontology for Semantic Annotation of Study Description.

    Science.gov (United States)

    Sahoo, Satya S; Valdez, Joshua; Rueschman, Michael

    2016-01-01

    Scientific reproducibility is key to scientific progress as it allows the research community to build on validated results, protect patients from potentially harmful trial drugs derived from incorrect results, and reduce wastage of valuable resources. The National Institutes of Health (NIH) recently published a systematic guideline titled "Rigor and Reproducibility " for supporting reproducible research studies, which has also been accepted by several scientific journals. These journals will require published articles to conform to these new guidelines. Provenance metadata describes the history or origin of data and it has been long used in computer science to capture metadata information for ensuring data quality and supporting scientific reproducibility. In this paper, we describe the development of Provenance for Clinical and healthcare Research (ProvCaRe) framework together with a provenance ontology to support scientific reproducibility by formally modeling a core set of data elements representing details of research study. We extend the PROV Ontology (PROV-O), which has been recommended as the provenance representation model by World Wide Web Consortium (W3C), to represent both: (a) data provenance, and (b) process provenance. We use 124 study variables from 6 clinical research studies from the National Sleep Research Resource (NSRR) to evaluate the coverage of the provenance ontology. NSRR is the largest repository of NIH-funded sleep datasets with 50,000 studies from 36,000 participants. The provenance ontology reuses ontology concepts from existing biomedical ontologies, for example the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), to model the provenance information of research studies. The ProvCaRe framework is being developed as part of the Big Data to Knowledge (BD2K) data provenance project.

  15. A Semantic Query Transformation Approach Based on Ontology for Search Engine

    Directory of Open Access Journals (Sweden)

    SAJENDRA KUMAR

    2012-05-01

    Full Text Available These days we are using some popular web search engines for information retrieval in all areas, such engine are as Google, Yahoo!, and Live Search, etc. to obtain initial helpful information.Which information we retrieved via search engine may not be relevant to the search target in the search engine user's mind. When user not found relevant information he has to shortlist the results. Thesesearch engines use traditional search service based on "static keywords", which require the users to type in the exact keywords. This approach clearly puts the users in a critical situation of guessing the exact keyword. The users may want to define their search by using attributes of the search target. But the relevancy of results in most cases may not be satisfactory and the users may not be patient enough to browse through complete list of pages to get a relevant result. The reason behind this is the search engines performs search based on the syntax not on semantics. But they seemed to be less efficient to understand the relationship between the keywords which had an adverse effect on the results it produced. Semantic search engines – only solution to this; which returns concepts not documents according to user query matching. In This paper we proposed a semantic query interface which creates a semantic query according the user input query and study of current semantic search engine techniques for semantic search.

  16. Rapid annotation of anonymous sequences from genome projects using semantic similarities and a weighting scheme in gene ontology.

    Directory of Open Access Journals (Sweden)

    Paolo Fontana

    Full Text Available BACKGROUND: Large-scale sequencing projects have now become routine lab practice and this has led to the development of a new generation of tools involving function prediction methods, bringing the latter back to the fore. The advent of Gene Ontology, with its structured vocabulary and paradigm, has provided computational biologists with an appropriate means for this task. METHODOLOGY: We present here a novel method called ARGOT (Annotation Retrieval of Gene Ontology Terms that is able to process quickly thousands of sequences for functional inference. The tool exploits for the first time an integrated approach which combines clustering of GO terms, based on their semantic similarities, with a weighting scheme which assesses retrieved hits sharing a certain number of biological features with the sequence to be annotated. These hits may be obtained by different methods and in this work we have based ARGOT processing on BLAST results. CONCLUSIONS: The extensive benchmark involved 10,000 protein sequences, the complete S. cerevisiae genome and a small subset of proteins for purposes of comparison with other available tools. The algorithm was proven to outperform existing methods and to be suitable for function prediction of single proteins due to its high degree of sensitivity, specificity and coverage.

  17. Latent Semantic Learning with Structured Sparse Representation for Human Action Recognition

    CERN Document Server

    Lu, Zhiwu

    2011-01-01

    This paper proposes a novel latent semantic learning method for extracting high-level features (i.e. latent semantics) from a large vocabulary of abundant mid-level features (i.e. visual keywords) with structured sparse representation, which can help to bridge the semantic gap in the challenging task of human action recognition. To discover the manifold structure of midlevel features, we develop a spectral embedding approach to latent semantic learning based on L1-graph, without the need to tune any parameter for graph construction as a key step of manifold learning. More importantly, we construct the L1-graph with structured sparse representation, which can be obtained by structured sparse coding with its structured sparsity ensured by novel L1-norm hypergraph regularization over mid-level features. In the new embedding space, we learn latent semantics automatically from abundant mid-level features through spectral clustering. The learnt latent semantics can be readily used for human action recognition with ...

  18. From ontology selection and semantic web to an integrated information system for food-borne diseases and food safety.

    Science.gov (United States)

    Yan, Xianghe; Peng, Yun; Meng, Jianghong; Ruzante, Juliana; Fratamico, Pina M; Huang, Lihan; Juneja, Vijay; Needleman, David S

    2011-01-01

    Several factors have hindered effective use of information and resources related to food safety due to inconsistency among semantically heterogeneous data resources, lack of knowledge on profiling of food-borne pathogens, and knowledge gaps among research communities, government risk assessors/managers, and end-users of the information. This paper discusses technical aspects in the establishment of a comprehensive food safety information system consisting of the following steps: (a) computational collection and compiling publicly available information, including published pathogen genomic, proteomic, and metabolomic data; (b) development of ontology libraries on food-borne pathogens and design automatic algorithms with formal inference and fuzzy and probabilistic reasoning to address the consistency and accuracy of distributed information resources (e.g., PulseNet, FoodNet, OutbreakNet, PubMed, NCBI, EMBL, and other online genetic databases and information); (c) integration of collected pathogen profiling data, Foodrisk.org ( http://www.foodrisk.org ), PMP, Combase, and other relevant information into a user-friendly, searchable, "homogeneous" information system available to scientists in academia, the food industry, and government agencies; and (d) development of a computational model in semantic web for greater adaptability and robustness.

  19. Conception and Use of Ontologies for Indexing and Searching by Semantic Contents of Video Courses

    CERN Document Server

    Merzougui, Ghalia; Behaz, Amel

    2012-01-01

    Nowadays, the video documents like educational courses available on the web increases significantly. However, the information retrieval systems today can not return to the users (students or teachers) of parts of those videos that meet their exact needs expressed by a query consisting of semantic information. In this paper, we present a model of pedagogical knowledge of current videos. This knowledge is used throughout the process of indexing and semantic search segments instructional videos. Our experimental results show that the proposed approach is promising.

  20. A Patient with Difficulty of Object Recognition: Semantic Amnesia for Manipulable Objects

    Directory of Open Access Journals (Sweden)

    A. Yamadori

    1992-01-01

    Full Text Available We studied a patient who had recognition difficulty for manipulable objects. MRI showed a lesion in the left occipito-parietotemporal area. Differential diagnosis of agnosia, aphasia and apraxia is discussed. We believe this “object meaning amnesia” constitutes a distinct subtype of semantic amnesia.

  1. Reasoning and Ontologies for Personalized E-Learning in the Semantic Web

    Science.gov (United States)

    Henze, Nicola; Dolog, Peter; Nejdl, Wolfgang

    2004-01-01

    The challenge of the semantic web is the provision of distributed information with well-defined meaning, understandable for different parties. Particularly, applications should be able to provide individually optimized access to information by taking the individual needs and requirements of the users into account. In this paper we propose a…

  2. 基于本体结构的语义相似度计算%Semantic Similarity Measurement Based on Ontology

    Institute of Scientific and Technical Information of China (English)

    杨方颖; 蒋正翔; 张姗姗

    2013-01-01

    语义相似度是语义网络和信息检索领域的重要内容.本体结构为语义相似度计算提供了新的思路,但现有的方法都存在着不同程度的缺陷.为了提高已有方法的有效性,在分析语义相似度经典方法的基础上,充分利用本体的结构信息,综合考虑概念在本体图中的位置、语义距离,共享属性量和共享信息等因素,提出了一个基于本体结构的语义相似度算法.实验部分以维基百科中公开发布的氨基酸本体为例,通过与经典方法计算结果的对比,证明了算法的有效性.%Semantic similarity is one of the most important parts in domains of semantic networks and information retrieval.The structure of ontology provides a new perspective for semantic similarity measurement.However,there are varying degrees of defaults in the existing methods.In order to improve the effectiveness of the existing methods,a novel approach for semantic similarity measurement based on ontology construction is proposed after a deep research on various classical approaches.It takes into account many factors,including semantic distance,level,semantic coincidence degree and information content.In order to verify the effectiveness of the algorithm,some comparative experiments are conducted using the Wikipedia disclosed amino acid ontology as an example.

  3. 一种对语义网上本体查询和检索的新方法%Novel method for searching ontologies on semantic web

    Institute of Scientific and Technical Information of China (English)

    虞为; 曹加恒; 陈俊鹏

    2006-01-01

    In order to solve the problem of information retrieval on the semantic web,a new semantic information retrieval (SIR) model for searching ontologies on the semantic web is proposed.First,SIR transformed domain ontologies into global ontologies.Then semantic index terms were extracted from these global ontologies.Based on semantic index terms, logical inferences can be performed and the logical views of the concept can be obtained.These logical views represent the expanded meaning of the concept.Using logical views,SIR can perform the information retrieval and inferences based on the semantic relationships in the documents,not only on the syntactic analysis of the documents.SIR can significantly enhance the recall and precision of the information retrieval by the semantic inference.Finally,the practicability of the SIR model is analyzed.%针对语义网信息检索中存在的问题,提出了一个基于语义索引词的语义网信息检索模型SIR(semantic information retrieval).其核心思想是将领域本体转换成全局本体,并从全局本体中提取语义索引词.通过语义索引词进行语义推理,可得概念的逻辑视图.SIR通过语义索引词间的语义关系对网络资源进行检索,解决了在传统的基于关键字的信息检索中只能从句法上对关键字进行分析,无法根据信息资源中的语义关系进行检索的问题.最后分析了SIR的可用性,证明了SIR可极大地提高语义网上信息检索的查全率和查准率.

  4. Search of phenotype related candidate genes using gene ontology-based semantic similarity and protein interaction information: application to Brugada syndrome.

    Science.gov (United States)

    Massanet, Raimon; Gallardo-Chacon, Joan-Josep; Caminal, Pere; Perera, Alexandre

    2009-01-01

    This work presents a methodology for finding phenotype candidate genes starting from a set of known related genes. This is accomplished by automatically mining and organizing the available scientific literature using Gene Ontology-based semantic similarity. As a case study, Brugada syndrome related genes have been used as input in order to obtain a list of other possible candidate genes related with this disease. Brugada anomaly produces a typical alteration in the Electrocardiogram and carriers of the disease show an increased probability of sudden death. Results show a set of semantically coherent proteins that are shown to be related with synaptic transmission and muscle contraction physiological processes.

  5. Language engineering for the Semantic Web: a digital library for endangered languages. Endangered languages, Ontology, Digital library, Multimedia, EMELD, Intelligent querying and retrieval, ImageSpace

    Directory of Open Access Journals (Sweden)

    Lu Shiyong

    2004-01-01

    Full Text Available In this paper, we describe the effort undertaken at Wayne State University to preserve endangered languages using the state-of-the-art information technologies. In particular, we discuss the issues involved in such an effort, and present the architecture of a distributed digital library for endangered languages which will contain various data of endangered languages in the forms of text, image, video, audio and include advanced tools for intelligent cataloguing, indexing, searching and browsing information on languages and language analysis. We use various Semantic Web technologies such as XML, OLAC, ontologies so that our digital library becomes a useful linguistic resource on the Semantic Web.

  6. 云环境下的语义本体构建及其在语义检索中的应用%Semantic Ontology Construction and its Application of Semantic Retrieval in Cloud Environment

    Institute of Scientific and Technical Information of China (English)

    鲍文燕; 沈岑诚; 刘博

    2012-01-01

    With the wide application of cloud technology,semantic retrieval in cloud environment becomes a important research content,but semantic ontology must be constructed.This paper firstly put forward data deployment strategy based on the similarity,object data will be deployed to different virtual machine according to the structure similarity and semantic similarity of the concept.and then semantic ontology will be constructed respectively and the corresponding semantic retrieval algorithm is proposed.%随着云技术的广泛应用,云环境下的语义检索也逐渐成为重要的研究内容,而语义本体构建是首先需要解决的问题.本文首先提出了一种基于相似度计算的数据部署策略,综合考虑了概念之间的结构相似度和语义相似度,将对象数据最优化的部署到不同的虚拟机分别构建语义本体,并给出了相应的语义检索算法.

  7. Mandarin-Speaking Children’s Speech Recognition: Developmental Changes in the Influences of Semantic Context and F0 Contours

    Science.gov (United States)

    Zhou, Hong; Li, Yu; Liang, Meng; Guan, Connie Qun; Zhang, Linjun; Shu, Hua; Zhang, Yang

    2017-01-01

    The goal of this developmental speech perception study was to assess whether and how age group modulated the influences of high-level semantic context and low-level fundamental frequency (F0) contours on the recognition of Mandarin speech by elementary and middle-school-aged children in quiet and interference backgrounds. The results revealed different patterns for semantic and F0 information. One the one hand, age group modulated significantly the use of F0 contours, indicating that elementary school children relied more on natural F0 contours than middle school children during Mandarin speech recognition. On the other hand, there was no significant modulation effect of age group on semantic context, indicating that children of both age groups used semantic context to assist speech recognition to a similar extent. Furthermore, the significant modulation effect of age group on the interaction between F0 contours and semantic context revealed that younger children could not make better use of semantic context in recognizing speech with flat F0 contours compared with natural F0 contours, while older children could benefit from semantic context even when natural F0 contours were altered, thus confirming the important role of F0 contours in Mandarin speech recognition by elementary school children. The developmental changes in the effects of high-level semantic and low-level F0 information on speech recognition might reflect the differences in auditory and cognitive resources associated with processing of the two types of information in speech perception. PMID:28701990

  8. Generating application ontologies from reference ontologies.

    Science.gov (United States)

    Shaw, Marianne; Detwiler, Landon T; Brinkley, James F; Suciu, Dan

    2008-11-06

    The semantic web provides the possiblity of linking together large numbers of biomedical ontologies. Unfortunately, many of the biomedical ontologies that have been developed are domain-specific and do not share a common structure that will allow them to be easily combined. Reference ontologies provide the necessary ontological framework for linking together these smaller, specialized ontologies. We present extensions to the semantic web query language SparQL that will allow researchers to develop application ontologies that are derived from reference ontologies. We have modified the ARQ query processor to support subqueries, recursive subqueries, and Skolem functions for node creation. We demonstrate the utility of these extensions by deriving an application ontology from the Foundational Model of Anatomy.

  9. Age-Related Differences in Face Recognition: Neural Correlates of Repetition and Semantic Priming in Young and Older Adults

    Science.gov (United States)

    Wiese, Holger; Komes, Jessica; Tüttenberg, Simone; Leidinger, Jana; Schweinberger, Stefan R.

    2017-01-01

    Difficulties in person recognition are among the common complaints associated with cognitive ageing. The present series of experiments therefore investigated face and person recognition in young and older adults. The authors examined how within-domain and cross-domain repetition as well as semantic priming affect familiar face recognition and…

  10. 基于领域本体的语义合成研究%Research on Semantic Synthesis Based on Domain Ontology

    Institute of Scientific and Technical Information of China (English)

    林培金; 曹苏燕; 应捷

    2013-01-01

    为了在检索过程中全面挖掘用户查询信息,文中提出了一种基于领域本体的语义合成技术,该方法以文本为数据源,引用数据源和领域本体之间的映射关系来表达数据文本的语义.文章提出了一个语义合成模型,该模型由领域本体、关键词语义抽取、概念语义相似度计算及语义推理等相关技术模型组成.文中对该模型进行了实验验证,通过对实验结果进行分析推理可知,文中提出的基于领域本体的语义合成模型提高了检索系统的查准率和计算机处理信息的能力,从而也提高了用户的满意度.%To overall mining the user's query information in the retrieval system,a study of semantic synthesis is proposed based on domain ontology.The method uses text as data source,and the mapping relation between the data source and the domain ontology is refered to express semantic of the data text.The semantic synthesis model has been verified by experiments,which includes the relative technology models such as domain ontology,key words semantic extraction,concept semantic similarity calculation and semantic reasoning.The experiment results show that the precision rate of retrieval system,the process ability of the computer and the user satisfaction are all improved through studing on semantic synthesis based on domain ontology in this paper.

  11. Product Named Entity Recognition Based on Ontology%基于本体的产品命名实体识别研究

    Institute of Scientific and Technical Information of China (English)

    罗芳; 熊前兴; 肖敏

    2011-01-01

    论述了近年来国内外在常规命名实体识别方面研究工作的进展状况,针对其中最为关键的产品命名实体识别技术,考虑到领域本体对产品命名实体识别的支持,提出了将本体特征融入到统计模型中,结合词性特征、上下文特征,以及本体特征的多特征模型进行产品命名实体识别实验,实验结果证明,该方法能有效地提高产品命名实体识别的性能.%In recent years,there are a lot of research achievements in the field of NER(name entity recognition) , while PNER (product named entity recognition) is just starting. With the rapid development of e - commerce,PNER becomes one of the key techniques of intelligent e - commerce. In the view of supporting domain ontology to PNER, a method of PNER was proposed, which combined CRF(conditional random field) model with domain ontology as a semantic feature besides word and part - of -speech features. Experiments were conducted to compare the two kinds of feature templates, and results indicate that the method can effectively improve the performance of PNER.

  12. 基于领域本体的语义文本挖掘研究%Research on Semantic Text Mining Based on Domain Ontology

    Institute of Scientific and Technical Information of China (English)

    张玉峰; 何超

    2011-01-01

    为了提高文本挖掘的深度和精度,研究并提出了一种基于领域本体的语义文本挖掘模型.该模型利用语义角色标注进行语义分析,获取概念和概念间的语义关系,提高文本表示的准确度;针对传统的知识挖掘算法不能有效挖掘语义元数据库,设计了一种基于语义的模式挖掘算法挖掘文本深层的语义模式.实验结果表明,该模型能够挖掘文本数据库中的深层语义知识,获取的模式具有很强的潜在应用价值,设计的算法具有很强的适应性和可扩展性.%In order to improve the depth and accuracy of text mining, a semantic text mining model based on domain ontology is proposed. In this model, semantic role labeling is applied to semantic analysis so that the semantic relations can be extracted accurately. For the defect of traditional knowledge mining algorithms that can not effectively mine semantic meta database, an association patterns mining algorithm hased on semantic is designed and used to acquire the deep semantic association patterns from semantic meta database. Experimental results show that the model can mine deep semantic knowledge from text database. The pattern got has great potential applications, and the algorithm designed has strong adaptability and scalability.

  13. InteGO2: a web tool for measuring and visualizing gene semantic similarities using Gene Ontology.

    Science.gov (United States)

    Peng, Jiajie; Li, Hongxiang; Liu, Yongzhuang; Juan, Liran; Jiang, Qinghua; Wang, Yadong; Chen, Jin

    2016-08-31

    The Gene Ontology (GO) has been used in high-throughput omics research as a major bioinformatics resource. The hierarchical structure of GO provides users a convenient platform for biological information abstraction and hypothesis testing. Computational methods have been developed to identify functionally similar genes. However, none of the existing measurements take into account all the rich information in GO. Similarly, using these existing methods, web-based applications have been constructed to compute gene functional similarities, and to provide pure text-based outputs. Without a graphical visualization interface, it is difficult for result interpretation. We present InteGO2, a web tool that allows researchers to calculate the GO-based gene semantic similarities using seven widely used GO-based similarity measurements. Also, we provide an integrative measurement that synergistically integrates all the individual measurements to improve the overall performance. Using HTML5 and cytoscape.js, we provide a graphical interface in InteGO2 to visualize the resulting gene functional association networks. InteGO2 is an easy-to-use HTML5 based web tool. With it, researchers can measure gene or gene product functional similarity conveniently, and visualize the network of functional interactions in a graphical interface. InteGO2 can be accessed via http://mlg.hit.edu.cn:8089/ .

  14. Constructive Ontology Engineering

    Science.gov (United States)

    Sousan, William L.

    2010-01-01

    The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in…

  15. Constructive Ontology Engineering

    Science.gov (United States)

    Sousan, William L.

    2010-01-01

    The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in…

  16. Semantic Web Query on e-Governance Data and Designing Ontology for Agriculture Domain

    Directory of Open Access Journals (Sweden)

    Swaran Lata

    2013-07-01

    Full Text Available Indian agriculture has made rapid progress on the agricultural front during the past three decades and isin a queue of the major producer in the world. But still it has long way to go and meet challenges aheadsuch as communication, resources, and availability at right time at right place. The web has had an amazingexistence and it has been the driving force for a cause to grow information across boundaries, enablingeffective communication and 24x7 service availability all leading to a digital information based economythat we have today. Despite that, its direct influence has reached to a small percentage of human population.Since localization populated with India and the applications are translated and adapted for Indian users.With the possible localization of spread raw formatted Indian government data, at different locationsare thought to have integrated with each other using the internet web technology as – Semantic Web Network.

  17. DESIGN AND IMPLEMENTATION OF ONTOLOGY BASED ON SEMANTIC ANALYSIS FOR GIS APPLICATION

    Directory of Open Access Journals (Sweden)

    S.S Mantha

    2011-09-01

    Full Text Available The Agricultural Census information is a leading source of facts and figures about a country’s agricultural development. Such information is used by many who provide services to farmers and rural communities including federal, state and local governments, agribusinesses etc. Also such information when integrated with other agricultural surveys and statistics can help in monitoring progress towards the achievement of Millennium Development Goals (MDGs of a country. But such huge volumes of census data are available at various geo-spatial portals either in proprietary formats like shape files, .dat files etc or in form of database tables, word documents, PDF’s etc. In order to do analysis or to just see the progress of a particular area such huge datasheets have to be scanned. This paper provides solutions to various problems related to Geo-spatial Agricultural Census data in three aspects: (1 Storage / Organization of census data using enhanced methods such as ontologies. (2 Visualization of data using Google Maps and Column Charts. (3 Analysis of data using interactive methods like Column Charts.

  18. Semantic Web Query on E-Governance Data and Designing Ontology for Agriculture Domain

    Directory of Open Access Journals (Sweden)

    Swaran Lata

    2013-07-01

    Full Text Available Indian agriculture has made rapid progress on the a gricultural front during the past three decades and is in a queue of the major producer in the world. But still it has long way to go and meet challenges ahead such as communication, resour ces, and availability at right time at right place. The web has had an amazing existence and it has been the driving force for a cause to grow information across boundaries, enabling effect ive communication and 24x7 service availability all leading to a digital information b ased economy that we have today. Despite that, its direct influence has reached to a small percent age of human population. Since localization populated with India and the applications are trans lated and adapted for Indian users. With the possible localization of spread raw formatted India n government data, at different locations are thought to have integrated with each other using th e internet web technology as – Semantic Web Network

  19. SEMANTIC ENHANCED UDDI USING OWL-S PROFILE ONTOLOGY FOR THE AUTOMATIC DISCOVERY OF WEB SERVICES IN THE DOMAIN OF TELECOMMUNICATION

    Directory of Open Access Journals (Sweden)

    R. Lakshmana Kumar

    2014-01-01

    Full Text Available The current web services which are evolved in the telecom domain such as payment web services, Yellow pages web services, operator web services, weather web services are failed to bring down the semantic as they used to prove its syntactic description. The reason for bringing down the semantic description into already existing web services will invoke certain operations like automatic discovery of web services, automatic composition of the necessary services, automatic invocation of web services and automatic monitoring of the execution process. At present the web services in the domain of telecommunication is following the parlay X standard. The parlay X has given a set of standard web service API’s for the telecom. The each of the services will have its own interface, services and types In this study in order to bring down the semantic representation we have proposed an idea to enable the semantic through the upper ontology like OWL-S and then how to map OWL-S to UDDI registry and also we have discussed some of the issues that we have faced while mapping OWL-S into UDDI registry. So the approach which we are going to propose improves the accuracy of the telecommunication network services description, discovery and matching, unifies the semantic representation of telecommunications network and Internet services.

  20. 基于本体的语义检索系统的设计%Semantic Retrieval System Design Based on Ontology

    Institute of Scientific and Technical Information of China (English)

    向胜军; 赵一

    2011-01-01

    Currently, various searches in business websites on the Internet are based on the keyword search. It is widely known that the keyword search has its drawbacks-the low recall rate and low precision rate. With a comparative study between the traditional search technology and the semantic one, it is essential for the system that the Semantic Web, ontology and some related tools such as the Protege, the Jena and the SPARQL. With them, the ontology of flower essays and a semantic retrieval system have been established. In this retrieval system, the user can experience the advantages of the semantic retrieve by searching flower essays in both ways: the traditional one and the semantic one. It is also provided in this system that the simple reasoning function which can judge some statements about flowers.%因特网上现有的各种检索方法都是基于关键词的,而关键词检索的弊端就是它的低查全率和低准确率.在对比现有检索技术与语义检索技术之后,着重介绍了语义Web、本体以及相关的工具如Protégé、Jena以及SPARQL查询语言等,构建了一个花卉文献本体,开发出基于该本体的语义检索系统.该系统比较了传统检索与语义检索2种方式,验证了语义检索技术的优势所在,提供了简单的推理功能,可以对关于花卉的一些语句进行推理验证.

  1. OWL 2 Web Ontology Language: XML serialization

    NARCIS (Netherlands)

    Motik, B.; Patel-Schneider, P.; Bechhofer, S.; Cuenca Grau, B.; Fokoue, A.; Hoekstra, R.; Parsia, B.

    2008-01-01

    The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information writ

  2. Research on Semantic B/S Based on Dynamic Ontology%基于动态本体的语义 B/S研究

    Institute of Scientific and Technical Information of China (English)

    罗钧旻; 桑蓓蓓

    2014-01-01

    This article analyzed the B/S work processes based on this semantic structure and designed an evolution algorithm of the relevant dynamic ontologies after having presented a method to describe the semantic structure of website information and customer preferences on the basis of the mutual-description principle and dynamic ontology theory .So a kind of semantic B/S mode has been formed to provide a personalized service for internet users .%根据语义的互表性原理和动态本体理论,提出一种描述网站信息和客户偏好语义结构的方法,分析了基于这一语义结构的B/S工作过程,设计了相关动态本体的更新和演化算法,形成了一种具有语义的B/S模式,试图能为上网用户提供具有个性化的服务。

  3. The Role of Semantic Diversity in Word Recognition across Aging and Bilingualism

    Directory of Open Access Journals (Sweden)

    Brendan eJohns

    2016-05-01

    Full Text Available Frequency effects are pervasive in studies of language, with higher frequency words being recognized faster than lower frequency words. However, the exact nature of frequency effects has recently been questioned, with some studies finding that contextual information provides a better fit to lexical decision and naming data than word frequency (Adelman, Brown, & Quesada, 2006. Recent work has cemented the importance of these results by demonstrating that a measure of the semantic diversity of the contexts that a word occurs provides a powerful measure to account for variability in word recognition latency (Jones, Jones, & Recchia, 2012; Johns, et al., 2012; Johns, Dye, & Jones, in press. The goal of the current study is to extend this measure to examine bilingualism and aging, where multiple theories use frequency of occurrence of linguistic constructs as central to accounting for empirical results (Gollan, Montoya, Cera, & Sandoval, 2008; Ramscar, Hendrix, Shaoul, Milin, & Baayen, 2014. A lexical decision experiment was conducted with 4 groups of subjects: younger and older monolinguals and bilinguals. Consistent with past results, a semantic diversity variable accounted for the greatest amount of variance in the latency data. In addition, the pattern of fits of semantic diversity across multiple corpora suggests that bilinguals and older adults are more sensitive to semantic diversity information than younger monolinguals.

  4. The Role of Semantic Diversity in Word Recognition across Aging and Bilingualism

    Science.gov (United States)

    Johns, Brendan T.; Sheppard, Christine L.; Jones, Michael N.; Taler, Vanessa

    2016-01-01

    Frequency effects are pervasive in studies of language, with higher frequency words being recognized faster than lower frequency words. However, the exact nature of frequency effects has recently been questioned, with some studies finding that contextual information provides a better fit to lexical decision and naming data than word frequency (Adelman et al., 2006). Recent work has cemented the importance of these results by demonstrating that a measure of the semantic diversity of the contexts that a word occurs in provides a powerful measure to account for variability in word recognition latency (Johns et al., 2012, 2015; Jones et al., 2012). The goal of the current study is to extend this measure to examine bilingualism and aging, where multiple theories use frequency of occurrence of linguistic constructs as central to accounting for empirical results (Gollan et al., 2008; Ramscar et al., 2014). A lexical decision experiment was conducted with four groups of subjects: younger and older monolinguals and bilinguals. Consistent with past results, a semantic diversity variable accounted for the greatest amount of variance in the latency data. In addition, the pattern of fits of semantic diversity across multiple corpora suggests that bilinguals and older adults are more sensitive to semantic diversity information than younger monolinguals. PMID:27458392

  5. The Onset and Time Course of Semantic Priming During Rapid Recognition of Visual Words.

    Science.gov (United States)

    Hoedemaker, Renske S; Gordon, Peter C

    2017-02-23

    In 2 experiments, we assessed the effects of response latency and task-induced goals on the onset and time course of semantic priming during rapid processing of visual words as revealed by ocular response tasks. In Experiment 1 (ocular lexical decision task), participants performed a lexical decision task using eye movement responses on a sequence of 4 words. In Experiment 2, the same words were encoded for an episodic recognition memory task that did not require a metalinguistic judgment. For both tasks, survival analyses showed that the earliest observable effect (divergence point [DP]) of semantic priming on target-word reading times occurred at approximately 260 ms, and ex-Gaussian distribution fits revealed that the magnitude of the priming effect increased as a function of response time. Together, these distributional effects of semantic priming suggest that the influence of the prime increases when target processing is more effortful. This effect does not require that the task include a metalinguistic judgment; manipulation of the task goals across experiments affected the overall response speed but not the location of the DP or the overall distributional pattern of the priming effect. These results are more readily explained as the result of a retrospective, rather than a prospective, priming mechanism and are consistent with compound-cue models of semantic priming. (PsycINFO Database Record

  6. The modulation of semantic transparency on the recognition memory for two-character Chinese words.

    Science.gov (United States)

    Han, Yi-Jhong; Huang, Shuo-Chieh; Lee, Chia-Ying; Kuo, Wen-Jui; Cheng, Shih-Kuen

    2014-11-01

    This study demonstrated that semantic transparency as a linguistic property modulates the recognition memory for two-character Chinese words, with opaque words (i.e., words whose meanings cannot be derived from constituent characters-e.g., "[/guang/, light][/gun/, stick]", bachelor) remembered better than transparent words (i.e., words whose meanings can be derived from constituent characters-e.g., "[/cha/, tea][/bei/, cup]", teacup). In Experiment 1, the participants made lexical decisions on transparent words, opaque words, and nonwords in the study and then engaged in an old/new recognition test. Experiment 2 employed a concreteness judgment as the encoding task to ensure equivalent semantic processing for opaque and transparent words. In Experiment 3, the neighborhood size of the two-character words was manipulated together with their semantic transparency. In all three experiments, opaque words were found to be better remembered than transparent words. We concluded that the conceptual incongruence between the meanings of a whole word and its constituent characters made opaque words more distinctive and, hence, better remembered than transparent words.

  7. Ontology Partitioning: Clustering Based Approach

    Directory of Open Access Journals (Sweden)

    Soraya Setti Ahmed

    2015-05-01

    Full Text Available The semantic web goal is to share and integrate data across different domains and organizations. The knowledge representations of semantic data are made possible by ontology. As the usage of semantic web increases, construction of the semantic web ontologies is also increased. Moreover, due to the monolithic nature of the ontology various semantic web operations like query answering, data sharing, data matching, data reuse and data integration become more complicated as the size of ontology increases. Partitioning the ontology is the key solution to handle this scalability issue. In this work, we propose a revision and an enhancement of K-means clustering algorithm based on a new semantic similarity measure for partitioning given ontology into high quality modules. The results show that our approach produces meaningful clusters than the traditional algorithm of K-means.

  8. Automating Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  9. Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  10. Optimized shape semantic graph representation for object understanding and recognition in point clouds

    Science.gov (United States)

    Ning, Xiaojuan; Wang, Yinghui; Meng, Weiliang; Zhang, Xiaopeng

    2016-10-01

    To understand and recognize the three-dimensional (3-D) objects represented as point cloud data, we use an optimized shape semantic graph (SSG) to describe 3-D objects. Based on the decomposed components of an object, the boundary surface of different components and the topology of components, the SSG gives a semantic description that is consistent with human vision perception. The similarity measurement of the SSG for different objects is effective for distinguishing the type of object and finding the most similar one. Experiments using a shape database show that the SSG is valuable for capturing the components of the objects and the corresponding relations between them. The SSG is not only suitable for an object without any loops but also appropriate for an object with loops to represent the shape and the topology. Moreover, a two-step progressive similarity measurement strategy is proposed to effectively improve the recognition rate in the shape database containing point-sample data.

  11. Arabic Phrase-Level Contextual Polarity Recognition to Enhance Sentiment Arabic Lexical Semantic Database Generation

    Directory of Open Access Journals (Sweden)

    Samir E. Abdelrahman

    2014-10-01

    Full Text Available Most of opinion mining works need lexical resources for opinion which recognize the polarity of words (positive/ negative regardless their contexts which called prior polarity. The word prior polarity may be changed when it is considered in its contexts, for example, positive words may be used in phrases expressing negative sentiments, or vice versa. In this paper, we aim at generating sentiment Arabic lexical semantic database having the word prior coupled with its contextual polarities and the related phrases. To do that, we study first the prior polarity effects of each word using our Sentiment Arabic Lexical Semantic Database on the sentence-level subjectivity and Support Vector Machine classifier. We then use the seminal English two-step contextual polarity phrase-level recognition approach to enhance word polarities within its contexts. Our results achieve significant improvement over baselines.

  12. Practical ontologies for information professionals

    CERN Document Server

    AUTHOR|(CDS)2071712

    2016-01-01

    Practical Ontologies for Information Professionals provides an introduction to ontologies and their development, an essential tool for fighting back against information overload. The development of robust and widely used ontologies is an increasingly important tool in the fight against information overload. The publishing and sharing of explicit explanations for a wide variety of conceptualizations, in a machine readable format, has the power to both improve information retrieval and identify new knowledge. This new book provides an accessible introduction to the following: * What is an ontology? Defining the concept and why it is increasingly important to the information professional * Ontologies and the semantic web * Existing ontologies, such as SKOS, OWL, FOAF, schema.org, and the DBpedia Ontology * Adopting and building ontologies, showing how to avoid repetition of work and how to build a simple ontology with Protege * Interrogating semantic web ontologies * The future of ontologies and the role of the ...

  13. Ontology-based semantic query for clinical trials%基于本体的临床试验数据语义查询

    Institute of Scientific and Technical Information of China (English)

    黄必清; 王涛; 朱鹏; 薛霄; 吴芸

    2012-01-01

    The extensive medical terminology used to describe clinical trials complicates Key words searches to locate resources.This paper presents an ontology-based semantic query system for clinical trial descriptions.This system uses the Web ontology language(OWL) to create the ontology based on ICD-10 and ICMJE(the ontology includes a clinical trial class and a disease class),retrieves clinical trial data from ClinicalTrials.gov,annotates the data as instances of the clinical trial class and creates relationships between the clinical trials and diseases to enable structured semantic clinical trial queries using SPARQL.Through this method,users can use disease and property Key words to express the structured semantic query and locate the resources.The query conditions generated by this method more accurately meet the user's needs than traditional queries.%临床试验数据的描述中多自然语言、多专业医学术语的特点使得用户难以通过自定义的关键字快速定位所需的资源。该文采用基于本体的方法实现对于临床试验数据的语义查询。该系统的实现步骤如下:使用OWL(Web on-tology language)构建基于ICD-10和ICMJE标准的本体,包含疾病和临床试验类;从Clinical Trials注册库获取临床试验数据,标注为本体中的临床试验类实例;建立临床试验实例与疾病实例的联系;借助SPARQL实现对于临床试验数据结构化的查询。使用上述方法,用户能够通过疾病实例和相关属性的关键字,表达结构化的语义查询条件,精确定位所需的临床试验。与传统的仅基于关键字匹配的查询方法相比,该方法所表达的查询条件能够更加准确地描述用户的查询需求。

  14. Research on the Technology of Ontology in Semantic Web%语义Web上的Ontology技术研究

    Institute of Scientific and Technical Information of China (English)

    梁新月

    2009-01-01

    分析了本体Ontology 及语义Web 之间的关系.阐述了Ontology 在语义Web 中的应用方向,通过实例研究了Ontology 在信息检索中的具体应用;展望了语义Web上的Ontology技术未来的研究方向.

  15. Meaningful Memory in Acute Anorexia Nervosa Patients-Comparing Recall, Learning, and Recognition of Semantically Related and Semantically Unrelated Word Stimuli.

    Science.gov (United States)

    Terhoeven, Valentin; Kallen, Ursula; Ingenerf, Katrin; Aschenbrenner, Steffen; Weisbrod, Matthias; Herzog, Wolfgang; Brockmeyer, Timo; Friederich, Hans-Christoph; Nikendei, Christoph

    2017-03-01

    It is unclear whether observed memory impairment in anorexia nervosa (AN) depends on the semantic structure (categorized words) of material to be encoded. We aimed to investigate the processing of semantically related information in AN. Memory performance was assessed in a recall, learning, and recognition test in 27 adult women with AN (19 restricting, 8 binge-eating/purging subtype; average disease duration: 9.32 years) and 30 healthy controls using an extended version of the Rey Auditory Verbal Learning Test, applying semantically related and unrelated word stimuli. Short-term memory (immediate recall, learning), regardless of semantics of the words, was significantly worse in AN patients, whereas long-term memory (delayed recall, recognition) did not differ between AN patients and controls. Semantics of stimuli do not have a better effect on memory recall in AN compared to CO. Impaired short-term versus long-term memory is discussed in relation to dysfunctional working memory in AN. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2016 John Wiley & Sons, Ltd and Eating Disorders Association.

  16. Get rich quick: the signal to respond procedure reveals the time course of semantic richness effects during visual word recognition.

    Science.gov (United States)

    Hargreaves, Ian S; Pexman, Penny M

    2014-05-01

    According to several current frameworks, semantic processing involves an early influence of language-based information followed by later influences of object-based information (e.g., situated simulations; Santos, Chaigneau, Simmons, & Barsalou, 2011). In the present study we examined whether these predictions extend to the influence of semantic variables in visual word recognition. We investigated the time course of semantic richness effects in visual word recognition using a signal-to-respond (STR) paradigm fitted to a lexical decision (LDT) and a semantic categorization (SCT) task. We used linear mixed effects to examine the relative contributions of language-based (number of senses, ARC) and object-based (imageability, number of features, body-object interaction ratings) descriptions of semantic richness at four STR durations (75, 100, 200, and 400ms). Results showed an early influence of number of senses and ARC in the SCT. In both LDT and SCT, object-based effects were the last to influence participants' decision latencies. We interpret our results within a framework in which semantic processes are available to influence word recognition as a function of their availability over time, and of their relevance to task-specific demands.

  17. Feature activation during word recognition: action, visual, and associative-semantic priming effects.

    Science.gov (United States)

    Lam, Kevin J Y; Dijkstra, Ton; Rueschemeyer, Shirley-Ann

    2015-01-01

    Embodied theories of language postulate that language meaning is stored in modality-specific brain areas generally involved in perception and action in the real world. However, the temporal dynamics of the interaction between modality-specific information and lexical-semantic processing remain unclear. We investigated the relative timing at which two types of modality-specific information (action-based and visual-form information) contribute to lexical-semantic comprehension. To this end, we applied a behavioral priming paradigm in which prime and target words were related with respect to (1) action features, (2) visual features, or (3) semantically associative information. Using a Go/No-Go lexical decision task, priming effects were measured across four different inter-stimulus intervals (ISI = 100, 250, 400, and 1000 ms) to determine the relative time course of the different features. Notably, action priming effects were found in ISIs of 100, 250, and 1000 ms whereas a visual priming effect was seen only in the ISI of 1000 ms. Importantly, our data suggest that features follow different time courses of activation during word recognition. In this regard, feature activation is dynamic, measurable in specific time windows but not in others. Thus the current study (1) demonstrates how multiple ISIs can be used within an experiment to help chart the time course of feature activation and (2) provides new evidence for embodied theories of language.

  18. Feature activation during word recognition: action, visual, and associative-semantic priming effects

    Directory of Open Access Journals (Sweden)

    Kevin J.Y. Lam

    2015-05-01

    Full Text Available Embodied theories of language postulate that language meaning is stored in modality-specific brain areas generally involved in perception and action in the real world. However, the temporal dynamics of the interaction between modality-specific information and lexical-semantic processing remain unclear. We investigated the relative timing at which two types of modality-specific information (action-based and visual-form information contribute to lexical-semantic comprehension. To this end, we applied a behavioral priming paradigm in which prime and target words were related with respect to (1 action features, (2 visual features, or (3 semantically associative information. Using a Go/No-Go lexical decision task, priming effects were measured across four different inter-stimulus intervals (ISI = 100 ms, 250 ms, 400 ms, and 1,000 ms to determine the relative time course of the different features . Notably, action priming effects were found in ISIs of 100 ms, 250 ms, and 1,000 ms whereas a visual priming effect was seen only in the ISI of 1,000 ms. Importantly, our data suggest that features follow different time courses of activation during word recognition. In this regard, feature activation is dynamic, measurable in specific time windows but not in others. Thus the current study (1 demonstrates how multiple ISIs can be used within an experiment to help chart the time course of feature activation and (2 provides new evidence for embodied theories of language.

  19. Towards automated biomedical ontology harmonization.

    Science.gov (United States)

    Uribe, Gustavo A; Lopez, Diego M; Blobel, Bernd

    2014-01-01

    The use of biomedical ontologies is increasing, especially in the context of health systems interoperability. Ontologies are key pieces to understand the semantics of information exchanged. However, given the diversity of biomedical ontologies, it is essential to develop tools that support harmonization processes amongst them. Several algorithms and tools are proposed by computer scientist for partially supporting ontology harmonization. However, these tools face several problems, especially in the biomedical domain where ontologies are large and complex. In the harmonization process, matching is a basic task. This paper explains the different ontology harmonization processes, analyzes existing matching tools, and proposes a prototype of an ontology harmonization service. The results demonstrate that there are many open issues in the field of biomedical ontology harmonization, such as: overcoming structural discrepancies between ontologies; the lack of semantic algorithms to automate the process; the low matching efficiency of existing algorithms; and the use of domain and top level ontologies in the matching process.

  20. 语义Web环境中基于本体推理的协同标注%Collaborative Annotation Based on Ontology Reasoning in Semantic Web Environment

    Institute of Scientific and Technical Information of China (English)

    祝锡永; 周益辉; 李晟

    2012-01-01

    Based on Web Collaborative Annotation Systems available, The paper first analyzes the common features of the tags in resource documents and context awareness to extend the concept group of tags and to map with their ontologies, then uses ontology reasoning to enrich the semantic of tags, to mine for implied semantic information, and to describe the internal relationships between documents, finally distinguishes the Pseudo-relevance among different documents in order to improve the accuracy of knowledge retrieval and knowledge recommendation as well as the flow of knowledge among subjects.%在已有的Web协同标注系统的基础上,通过对资源文档的标签进行共性分析以及上下文情境感知,以此来扩展标签的概念组,并将其与相关本体进行映射;利用本体推理技术来丰富标签的语义性,挖掘出文档隐含的语义信息,发现文档间所存在的内部关联,同时鉴别不同文档之间是否存在着伪关联,以此提高知识检索与知识推荐的准确性以及主体间的知识共享水平.

  1. Semantic Data Integration and Ontology Use within the Global Earth Observation System of Systems (GEOSS) Global Water Cycle Data Integration System

    Science.gov (United States)

    Pozzi, W.; Fekete, B.; Piasecki, M.; McGuinness, D.; Fox, P.; Lawford, R.; Vorosmarty, C.; Houser, P.; Imam, B.

    2008-12-01

    The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so

  2. Foundations of semantic web technologies

    CERN Document Server

    Hitzler, Pascal; Rudolph, Sebastian

    2009-01-01

    The Quest for Semantics Building Models Calculating with Knowledge Exchanging Information Semanic Web Technologies RESOURCE DESCRIPTION LANGUAGE (RDF)Simple Ontologies in RDF and RDF SchemaIntroduction to RDF Syntax for RDF Advanced Features Simple Ontologies in RDF Schema Encoding of Special Data Structures An ExampleRDF Formal Semantics Why Semantics? Model-Theoretic Semantics for RDF(S) Syntactic Reasoning with Deduction Rules The Semantic Limits of RDF(S)WEB ONTOLOGY LANGUAGE (OWL) Ontologies in OWL OWL Syntax and Intuitive Semantics OWL Species The Forthcoming OWL 2 StandardOWL Formal Sem

  3. Research on Ontology-based of Semantic Retrieval Key Technology of Educational Resources%基于本体的教育资源语义检索关键技术研究

    Institute of Scientific and Technical Information of China (English)

    刘琪; 王小正; 王磊

    2014-01-01

    该文对基于本体的语义检索涉及的几个关键技术进行了深入探究,包括教育资源本体的构建、本体数据的存储等。并在此基础上设计出基于本体的自适应Web信息抽取模型和本体数据及实例数据存储模型。%This paper studies Ontology-Based of Semantic Retrieval Key Technology of Educational Resources, which includes ontology of educational resources construction and ontology data storage. Finally, the designs of adaptive web information extrac-tion model based on ontology and ontology data and instance data storage model are described.

  4. Method of semantic similarity calculation for component testing ontology%针对构件测试本体的语义相似度计算方法

    Institute of Scientific and Technical Information of China (English)

    韩仙玉; 姜瑛

    2011-01-01

    Concerning the problem that some results are easily leaked while the component testing ontology is retrieved using the existed calculation method of ontology semantic similarity, a similarity calculation method based on concept and attribute was proposed to improve the retrieval efficiency of component testing information. Firstly, the structure, hierarchy,the number of offspring nodes and ancestor nodes of concept were used to calculate the concept similarity. Then, the attribute similarity was calculated based on the concept similarity of the attributes and its data type similarity. Finally, the concept similarity and attribute similarity were combined to calculate the comprehensive ontology semantic similarity. The experimental results indicate that the similarity calculation method can be applied in component testing and other domains effectively.%为了提高构件测试信息的检索效率,针对现有本体语义相似度计算方法作用于构件测试本体时容易出现漏检的问题,提出一种结合本体概念和属性的综合语义相似度计算方法.该方法首先结合概念的结构、层次、子代节点个数和祖先节点个数等因素计算概念相似度;然后,结合属性的概念相似度和数据类型相似度计算属性相似度;最后,综合概念相似度和属性相似度计算本体的语义相似度.实验表明该方法可以有效应用于构件测试领域及其他领域的信息检索.

  5. Geospatial semantic web

    CERN Document Server

    Zhang, Chuanrong; Li, Weidong

    2015-01-01

    This book covers key issues related to Geospatial Semantic Web, including geospatial web services for spatial data interoperability; geospatial ontology for semantic interoperability; ontology creation, sharing, and integration; querying knowledge and information from heterogeneous data source; interfaces for Geospatial Semantic Web, VGI (Volunteered Geographic Information) and Geospatial Semantic Web; challenges of Geospatial Semantic Web; and development of Geospatial Semantic Web applications. This book also describes state-of-the-art technologies that attempt to solve these problems such as WFS, WMS, RDF, OWL, and GeoSPARQL, and demonstrates how to use the Geospatial Semantic Web technologies to solve practical real-world problems such as spatial data interoperability.

  6. 基于本体的语义查询扩展应用研究%Application Research of Semantic Query Expansion Based on Ontology

    Institute of Scientific and Technical Information of China (English)

    王红霞

    2016-01-01

    传统的基于关键词匹配的信息检索方式已无法满足智慧城市建设进程中海量数据处理的要求,而基于本体的语义查询扩展智能化搜索技术借助于本体的语义信息与扩展推理使查询条件更符合用户意图,能够提高查全率和查准率,优化检索结果.在本体语义查询扩展技术的研究基础上,使用主流的本体编辑工具Protégé创建了一个"计算机"领域的本体,并根据现实需要进行规则修改,最终将其应用于智慧城市远程教育资源的个性化搜索中,能取得较理想的效果.%With the rapid development of smart city, the traditional search method based on key words can 't satisfy users. Semantic query expansion based on ontology is an important intelligent search technique which with the help of semantic information and expansion reasoning. The precision and recall can be improved and the research result can be optimized. This article studies carefully the semantic query expansion theory, built domain ontology of the computer science based on Protégé and Chinese Library Classification. In the same way, the rules are modified according to the reality. Eventually, the query expansion was used to distance education resources of smart city for personalized search with good effect.

  7. Semantic Query Expansion Based on Multilingual Ontology%基于多语本体的语义查询扩展研究

    Institute of Scientific and Technical Information of China (English)

    司莉; 潘秋玉

    2016-01-01

    查询扩展是改善信息检索结果的有效方法。针对用户获取多语言信息的需求以及当前跨语言信息检索存在的翻译歧异性问题,提出一种基于多语本体的语义查询扩展方法,介绍其基本原理、查询扩展模型及实现过程,使跨语言信息检索从字符匹配变成语义层面的匹配,实现跨语言信息检索中的查询扩展,以提高多语言信息检索的查全率和查准率。%Query expansion is an effective method to enhance information retrieval performance. Aiming at the requirements of acquiring multilingual information and solving the problems of semantic disambiguation of cross language information retrieval (CLIR), the article proposed a new semantic query expansion method based on multilingual ontology, and introduced its fundamentals, model and realization process, to turn character-matching into semantic matching for CLIR, implementing query expansion in CLIR, which may optimize system’s recal and precision.

  8. Effects of Semantic Features on Machine Learning-Based Drug Name Recognition Systems: Word Embeddings vs. Manually Constructed Dictionaries

    Directory of Open Access Journals (Sweden)

    Shengyu Liu

    2015-12-01

    Full Text Available Semantic features are very important for machine learning-based drug name recognition (DNR systems. The semantic features used in most DNR systems are based on drug dictionaries manually constructed by experts. Building large-scale drug dictionaries is a time-consuming task and adding new drugs to existing drug dictionaries immediately after they are developed is also a challenge. In recent years, word embeddings that contain rich latent semantic information of words have been widely used to improve the performance of various natural language processing tasks. However, they have not been used in DNR systems. Compared to the semantic features based on drug dictionaries, the advantage of word embeddings lies in that learning them is unsupervised. In this paper, we investigate the effect of semantic features based on word embeddings on DNR and compare them with semantic features based on three drug dictionaries. We propose a conditional random fields (CRF-based system for DNR. The skip-gram model, an unsupervised algorithm, is used to induce word embeddings on about 17.3 GigaByte (GB unlabeled biomedical texts collected from MEDLINE (National Library of Medicine, Bethesda, MD, USA. The system is evaluated on the drug-drug interaction extraction (DDIExtraction 2013 corpus. Experimental results show that word embeddings significantly improve the performance of the DNR system and they are competitive with semantic features based on drug dictionaries. F-score is improved by 2.92 percentage points when word embeddings are added into the baseline system. It is comparative with the improvements from semantic features based on drug dictionaries. Furthermore, word embeddings are complementary to the semantic features based on drug dictionaries. When both word embeddings and semantic features based on drug dictionaries are added, the system achieves the best performance with an F-score of 78.37%, which outperforms the best system of the DDIExtraction 2013

  9. Interference Effects as a Function of Semantic Similarity in the Translation Recognition Task in Bilinguals of Catalan and Spanish

    Science.gov (United States)

    Moldovan, Cornelia D.; Sanchez-Casas, Rosa; Demestre, Josep; Ferre, Pilar

    2012-01-01

    Previous evidence has shown that word pairs that are either related in form (e.g., "ruc-berro"; donkey-watercress) or very closely semantically related (e.g., "ruc-caballo", donkey-horse) produce interference effects in a translation recognition task (Ferre et al., 2006; Guasch et al., 2008). However, these effects are not…

  10. Universal Dimensions of Meaning Derived from Semantic Relations among Words and Senses: Mereological Completeness vs. Ontological Generality

    Directory of Open Access Journals (Sweden)

    Alexei V. Samsonovich

    2014-07-01

    Full Text Available A key to semantic analysis is a precise and practically useful definition of meaning that is general for all domains of knowledge. We previously introduced the notion of weak semantic map: a metric space allocating concepts along their most general (universal semantic characteristics while at the same time ignoring other, domain-specific aspects of their meanings. Here we address questions of the number, quality, and mutual independence of the weak semantic dimensions. Specifically, we employ semantic relationships not previously used for weak semantic mapping, such as holonymy/meronymy (“is-part/member-of”, and we compare maps constructed from word senses to those constructed from words. We show that the “completeness” dimension derived from the holonym/meronym relation is independent of, and practically orthogonal to, the “abstractness” dimension derived from the hypernym-hyponym (“is-a” relation, while both dimensions are orthogonal to the maps derived from synonymy and antonymy. Interestingly, the choice of using relations among words vs. senses implies a non-trivial trade-off between rich and unambiguous information due to homonymy and polysemy. The practical utility of the new and prior dimensions is illustrated by the automated evaluation of different kinds of documents. Residual analysis of available linguistic resources, such as WordNet, suggests that the number of universal semantic dimensions representable in natural language may be finite. Their complete characterization, as well as the extension of results to non-linguistic materials, remains an open challenge.

  11. Semantic Virtual Environment Querying and Reasoning Model Based on Ontology%基于本体的语义虚拟环境查询与推理模型

    Institute of Scientific and Technical Information of China (English)

    刘一松; 王艳莲

    2014-01-01

    当前将本体引入到语义虚拟环境的研究,只是将领域本体的可视化信息用本体表示,并未发挥本体本身具有的优势。为此,提出一种基于本体的语义虚拟环境查询与推理模型。利用OWL语言统一描述虚拟场景图形内容与语义信息,并分别对两者进行查询,在图形内容查询过程中引入本体的推理方法推理出隐含的图形内容信息,然后查询需要的信息。在语义信息查询时引入语义搜索方法,利用基于语义距离计算本体概念相似度的方法计算语义虚拟环境本体中类之间的相似度,搜索与被查询实例语义相似度最大的实例,并借助推理找出其间的关系。对语义虚拟家具商店进行本体的查询与推理,结果证明了该模型的可行性。%The research on introducing ontology into semantic virtual environment at present, only uses ontology to visualize the specific domain ontology,and does not display ontology’ s advantage. Aiming at this problem,this paper proposes a semantic virtual environment querying and reasoning model based on ontology. The web ontology language named OWL is used to uniformly describe the graphic content and semantic information,and query them respectively. In the process of querying graphic content,it introduces reasoning method of ontology to get out the connotative graphic content,then queries the information which is needed. In the process of querying semantic information, it introduces semantic search method, according to the method which is based on semantic distance to compute ontology concept similarity to compute the similarity between classes in the semantic virtual environment ontology, then searches the instance which has the maximum similarity with the queried instance,and finds out the relation between them with the help of reasoning. This model makes ontology play bigger role in semantic virtual environment,and the feasibility of this Mapping Ontology

  12. Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

    Science.gov (United States)

    Urbain, Jay

    2015-12-01

    We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic patients over time. The system was originally developed for the 2014 i2b2 Challenges in Natural Language in Clinical Data. The system's strengths included a high level of accuracy for identifying named entities associated with heart disease risk factor events. The system's primary weakness was due to inaccuracies when characterizing the attributes of some events. For example, determining the relative time of an event with respect to the record date, whether an event is attributable to the patient's history or the patient's family history, and differentiating between current and prior smoking status. We believe these inaccuracies were due in large part to the lack of an effective approach for integrating context into our event detection model. To address these inaccuracies, we explore the addition of a distributional semantic model for characterizing contextual evidence of heart disease risk factor events. Using this semantic model, we raise our initial 2014 i2b2 Challenges in Natural Language of Clinical data F1 score of 0.838 to 0.890 and increased precision by 10.3% without use of any lexicons that might bias our results.

  13. 采用Ontology和树的语义冲突消除法%Semantic Conflict Resolution Method by Applying Ontology and Tree

    Institute of Scientific and Technical Information of China (English)

    李俊州; 茹秀娟

    2013-01-01

    Semantic information integration aims to shield semi-structured heterogeneous and distributed data,and to provide users with a wider range of precise data sharing.In order to solve the semantic conflict of information integration,Ontology is used to describe global data concept,and tree structure is employed to describe the concept of the local data.The logic definition method of the data is proposed and adopted.The similarity is used to calculate for data matching semantic integration in the match.And the homologous mapping algorithm of semantic information integration is defined.Experimental results verify the correctness of this method.%语义信息集成是目前屏蔽数据之间半结构性、异构性和分布性的主要方法,其目的是为用户提供最大范围的精确数据.本文以解决信息集成中的语义冲突为目的,采用Ontology描述全局数据概念、树型结构描述局部数据概念.在此基础上,给出数据的逻辑定义方法,利用相似度计算匹配值来实现数据在语义集成中的匹配,并描述语义信息集成中的映射算法.最后,给出了实验数据和算法执行结果,验证了此方法的正确性.

  14. Marine Planning and Service Platform: specific ontology based semantic search engine serving data management and sustainable development

    Science.gov (United States)

    Manzella, Giuseppe M. R.; Bartolini, Andrea; Bustaffa, Franco; D'Angelo, Paolo; De Mattei, Maurizio; Frontini, Francesca; Maltese, Maurizio; Medone, Daniele; Monachini, Monica; Novellino, Antonio; Spada, Andrea

    2016-04-01

    : the whole document gets parsed to extract the words which are more meaningful for the main argument of the document, and applies the extraction in the form of N-grams (mono-grams, bi-grams, tri-grams). • MAPS database - This module is a simple database which contains all the N-grams used by MAPS (physical parameters from SeaDataNet vocabularies) to define our marine "ontology". • Relation identifier - This module performs the most important task of identifying relationships between the N-gram extracted from the text by the parser and the provided oceanographic terminology. It checks N-grams supplied by the Syntactic parser and then matches them with the terms stored in the MAPS database. Found matches are returned back to the parser with flexed form appearing in the source text. • A "relaxed" extractor - This option can be activated when the search engine is launched. It was introduced to give the user a chance to create new N-grams combining existing mono-grams and bi-grams in the database with rich-words found within the source text. The innovation of a semantic engine lies in the fact that the process is not just about the retrieval of already known documents by means of a simple term query but rather the retrieval of a population of documents whose existence was unknown. The system answers by showing a screenshot of results ordered according to the following criteria: • Relevance - of the document with respect to the concept that is searched • Date - of publication of the paper • Source - data provider as defined in the SeaDataNet Common Data Index • Matrix - environmental matrices as defined in the oceanographic field • Geographic area - area specified in the text • Clustering - the process of organizing objects into groups whose members are similar The clustering returns as the output the related documents. For each document the MAPS visualization provides: • Title, author, source/provider of data, web address • Tagging of key terms or

  15. Ontologies in biological data visualization.

    Science.gov (United States)

    Carpendale, Sheelagh; Chen, Min; Evanko, Daniel; Gehlenborg, Nils; Gorg, Carsten; Hunter, Larry; Rowland, Francis; Storey, Margaret-Anne; Strobelt, Hendrik

    2014-01-01

    In computer science, an ontology is essentially a graph-based knowledge representation in which each node corresponds to a concept and each edge specifies a relation between two concepts. Ontological development in biology can serve as a focus to discuss the challenges and possible research directions for ontologies in visualization. The principle challenges are the dynamic and evolving nature of ontologies, the ever-present issue of scale, the diversity and richness of the relationships in ontologies, and the need to better understand the relationship between ontologies and the data analysis tasks scientists wish to support. Research directions include visualizing ontologies; visualizing semantically or ontologically annotated texts, documents, and corpora; automated generation of visualizations using ontologies; and visualizing ontological context to support search. Although this discussion uses issues of ontologies in biological data visualization as a springboard, these topics are of general relevance to visualization.

  16. Linguistic Context Versus Semantic Competition in Word Recognition by Younger and Older Adults With Cochlear Implants.

    Science.gov (United States)

    Amichetti, Nicole M; Atagi, Eriko; Kong, Ying-Yee; Wingfield, Arthur

    2017-07-11

    greater degree of interference from other words that might also be activated by the context, with negative effects on ease of word recognition. These results are consistent with an age-related inhibition deficit extending to the domain of semantic constraints on word recognition.

  17. Comment on Semantic Web Based on Ontology%基于本体的语义Web浅谈

    Institute of Scientific and Technical Information of China (English)

    王睿

    2011-01-01

    Base on the analysis of limitatiom of the Word Wide Web technology, this paper discussed semantic Web and the origin of the semantic Web. Key technologies of semantic are introduced, and then application of semantic Web and development prospect are expound.%文章分析了现有万维网技术的局限性并在此基础上对语义Web进行了系统论述,着重介绍了语义Web的起源及关键技术XML、RDF(S)和本体,分析和论述了语义Web技术的应用及发展前景。

  18. Audio Semantic Retrieval Model Based on Ontology%基于本体的音频语义检索模型

    Institute of Scientific and Technical Information of China (English)

    张小莉; 许东芳

    2014-01-01

    This paper analyzes the existing problems in currently used audio retrieval,puts forward a method for marking the semantic annotation automatically for the voice data, and establishes a new retrieval model of audio ontology repository, and prospects the future research directions.%通过分析现有音频检索中存在的问题,提出了一种对语音数据进行语义自动标注的方法,建立了一种新的音频本体库的检索模型,并对今后的研究方向进行了展望。

  19. Improving the measurement of semantic similarity between gene ontology terms and gene products: insights from an edge- and IC-based hybrid method.

    Directory of Open Access Journals (Sweden)

    Xiaomei Wu

    Full Text Available BACKGROUND: Explicit comparisons based on the semantic similarity of Gene Ontology terms provide a quantitative way to measure the functional similarity between gene products and are widely applied in large-scale genomic research via integration with other models. Previously, we presented an edge-based method, Relative Specificity Similarity (RSS, which takes the global position of relevant terms into account. However, edge-based semantic similarity metrics are sensitive to the intrinsic structure of GO and simply consider terms at the same level in the ontology to be equally specific nodes, revealing the weaknesses that could be complemented using information content (IC. RESULTS AND CONCLUSIONS: Here, we used the IC-based nodes to improve RSS and proposed a new method, Hybrid Relative Specificity Similarity (HRSS. HRSS outperformed other methods in distinguishing true protein-protein interactions from false. HRSS values were divided into four different levels of confidence for protein interactions. In addition, HRSS was statistically the best at obtaining the highest average functional similarity among human-mouse orthologs. Both HRSS and the groupwise measure, simGIC, are superior in correlation with sequence and Pfam similarities. Because different measures are best suited for different circumstances, we compared two pairwise strategies, the maximum and the best-match average, in the evaluation. The former was more effective at inferring physical protein-protein interactions, and the latter at estimating the functional conservation of orthologs and analyzing the CESSM datasets. In conclusion, HRSS can be applied to different biological problems by quantifying the functional similarity between gene products. The algorithm HRSS was implemented in the C programming language, which is freely available from http://cmb.bnu.edu.cn/hrss.

  20. The anterior temporal cortex is a primary semantic source of top-down influences on object recognition.

    Science.gov (United States)

    Chiou, Rocco; Lambon Ralph, Matthew A

    2016-06-01

    Perception emerges from a dynamic interplay between feed-forward sensory input and feedback modulation along the cascade of neural processing. Prior knowledge, a major form of top-down modulatory signal, benefits perception by enabling efficacious inference and resolving ambiguity, particularly under circumstances of degraded visual input. Despite semantic information being a potentially critical source of this top-down influence, to date, the core neural substrate of semantic knowledge (the anterolateral temporal lobe - ATL) has not been considered as a key component of the feedback system. Here we provide direct evidence of its significance for visual cognition - the ATL underpins the semantic aspect of object recognition, amalgamating sensory-based (amount of accumulated sensory input) and semantic-based (representational proximity between exemplars and typicality of appearance) influences. Using transcranial theta-burst stimulation combined with a novel visual identification paradigm, we demonstrate that the left ATL contributes to discrimination between visual objects. Crucially, its contribution is especially vital under situations where semantic knowledge is most needed for supplementing deficiency of input (brief visual exposure), discerning analogously-coded exemplars (close representational distance), and resolving discordance (target appearance violating the statistical typicality of its category). Our findings characterise functional properties of the ATL in object recognition: this neural structure is summoned to augment the visual system when the latter is overtaxed by challenging conditions (insufficient input, overlapped neural coding, and conflict between incoming signal and expected configuration). This suggests a need to revisit current theories of object recognition, incorporating the ATL that interfaces high-level vision with semantic knowledge.

  1. A semantics of love: Brief notes on desire and recognition in Georges Bataille

    Directory of Open Access Journals (Sweden)

    Herivelto Pereira de Souza

    2013-06-01

    , transgressive experiences points to a disruptive effect over the features of subjective arrangement, intersubjectively formed. That is why excitement and fear, pleasure and anguish intertwine in eroticism, and desire becomes the name of a fascinating and frightening ontological excess. It is this very paradoxical character that is decisive for Bataille, for if norms need their transgression in order to exert a subjective inscription, one should not take the passage from desire to recognition as just a progressive process towards a determined form of sociality. Bataille associates a certain Durkheimian heritage with a philosophy of life to account for a libidinal economy of recognition in which desire lies at its very core. This paper proposes a reflection on what is at stake in this conceptual operation, and on the significance of the peculiar enjoyment of norms to a rethinking of the particular aspirations of recognition in love relationships.

  2. Realist Ontology and Natural Processes: A Semantic Tool to Analyze the Presentation of the Osmosis Concept in Science Texts

    Science.gov (United States)

    Spinelli Barria, Michele; Morales, Cecilia; Merino, Cristian; Quiroz, Waldo

    2016-01-01

    In this work, we developed an ontological tool, based on the scientific realism of Mario Bunge, for the analysis of the presentation of natural processes in science textbooks. This tool was applied to analyze the presentation of the concept of osmosis in 16 chemistry and biology books at different educational levels. The results showed that more…

  3. Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology.

    Science.gov (United States)

    Malhotra, Ashutosh; Gündel, Michaela; Rajput, Abdul Mateen; Mevissen, Heinz-Theodor; Saiz, Albert; Pastor, Xavier; Lozano-Rubi, Raimundo; Martinez-Lapiscina, Elena H; Martinez-Lapsicina, Elena H; Zubizarreta, Irati; Mueller, Bernd; Kotelnikova, Ekaterina; Toldo, Luca; Hofmann-Apitius, Martin; Villoslada, Pablo

    2015-01-01

    In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.

  4. Ontologies for Bioinformatics

    Directory of Open Access Journals (Sweden)

    Agnieszka Leszczynski

    2008-01-01

    Full Text Available The past twenty years have witnessed an explosion of biological data in diverse database formats governed by heterogeneous infrastructures. Not only are semantics (attribute terms different in meaning across databases, but their organization varies widely. Ontologies are a concept imported from computing science to describe different conceptual frameworks that guide the collection, organization and publication of biological data. An ontology is similar to a paradigm but has very strict implications for formatting and meaning in a computational context. The use of ontologies is a means of communicating and resolving semantic and organizational differences between biological databases in order to enhance their integration. The purpose of interoperability (or sharing between divergent storage and semantic protocols is to allow scientists from around the world to share and communicate with each other. This paper describes the rapid accumulation of biological data, its various organizational structures, and the role that ontologies play in interoperability.

  5. The Research of Semantic Search Engine based on Ontology%基于ontology的语义搜索引擎研究

    Institute of Scientific and Technical Information of China (English)

    李延香; 袁辉

    2013-01-01

    This paper analyzes the search engine systems,designs a semantic search engine system architecture based on ontology.It not only merely based on a keyword retrieve,but also understand the meaning of content on the Web pages and carries out the semantic reasoning,perform complex search queries.It is certainly valuable for improving precision and recall rates of web retrieval.%在分析搜索引擎的基础上,提出了一种基于ontology的语义搜索引擎系统设想.这个搜索设想不仅能实现关键词的检索,还能让机器理解Web页面的内容、进行语义推理、完成更繁杂细致的搜索任务.将对于提高Web的查全率和查准率有一定的参考意义.

  6. Ontology-based approaches for cross-enterprise collaboration: a literature review on semantic business process management

    Science.gov (United States)

    Hoang, Hanh H.; Jung, Jason J.; Tran, Chi P.

    2014-11-01

    Based on an in-depth analysis of the existing approaches in applying semantic technologies to business process management (BPM) research in the perspective of cross-enterprise collaboration or so-called business-to-business integration, we analyse, discuss and compare methodologies, applications and best practices of the surveyed approaches with the proposed criteria. This article identifies various relevant research directions in semantic BPM (SBPM). Founded on the result of our investigation, we summarise the state of art of SBPM. We also address areas and directions for further research activities.

  7. Ontology Based Access Control

    Directory of Open Access Journals (Sweden)

    Özgü CAN

    2010-02-01

    Full Text Available As computer technologies become pervasive, the need for access control mechanisms grow. The purpose of an access control is to limit the operations that a computer system user can perform. Thus, access control ensures to prevent an activity which can lead to a security breach. For the success of Semantic Web, that allows machines to share and reuse the information by using formal semantics for machines to communicate with other machines, access control mechanisms are needed. Access control mechanism indicates certain constraints which must be achieved by the user before performing an operation to provide a secure Semantic Web. In this work, unlike traditional access control mechanisms, an "Ontology Based Access Control" mechanism has been developed by using Semantic Web based policies. In this mechanism, ontologies are used to model the access control knowledge and domain knowledge is used to create policy ontologies.

  8. 基于本体语义树的主题空间向量模型%Thematic VSM Based on Ontology Semantic Tree

    Institute of Scientific and Technical Information of China (English)

    卢承山

    2011-01-01

    Based on the traditional search model, combining the concept of ontology, this paper proposes a thematic network crawling model based on ontology semantic tree. Unlike the traditional keyword-based subject description methods, the model can describe a subject with semantic concept tree with which it is simple to describe tbe semantic relationships between concepts. On this basis, the paper presents a method to calculate the relevance of HTML pages and the topic. When analyzing the relevance of URL, it does not only analyze the relevance of link anchor text and the topic, but also analyzes the relevance of the link with an improved PageRank algorithm. Only when the relevance does not reach a given threshold will it download the page corresponding to the URL. This calculation method can greatly reduce unnecessary computational overhead, and make fully use of anchor text and link importance of information. Finally, it calculates the relevance of a web page which is not sure whether it is related to the topic, and ultimately determines whether this page should be collected or not.%在传统检索模型的基础上,结合本体的概念,提出一种基于本体语义树的主题空间向量模型,该模型能够用语义概念树描述一个主题,与传统基于关键词描述主题的方法不同,它能够描述概念之间的简单语义关系.在此基础上,给出HTML页面内容与主题相关度的计算方法.在分析URL的相关度时,不仅分析链接锚文本与主题相关度,还结合了改进的PageRank算法来分析链接的相关度.只有当链接相关度达不到给定的阀值时才会去下载链接对应的页面.这样的URL相关度计算方法可以大大减少不必要的计算开销,又可以充分地利用锚文本和链接重要度信息.最后还对那些不确定是否与主题相关的网页进行内容相关度计算,进而最终确定是否应该采集此网页.

  9. Addressing issues in foundational ontology mediation

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-09-01

    Full Text Available An approach in achieving semantic interoperability among heterogeneous systems is to offer infrastructure to assist with linking and integration using a foundational ontology. Due to the creation of multiple foundational ontologies, this also means...

  10. Format change and semantic relatedness effects on the ERP correlates of recognition: old pairs, new pairs, different stories.

    Science.gov (United States)

    Guillaume, Fabrice; Baier, Sophia; Bourgeois, Mélanie; Tinard, Sophie

    2016-12-28

    In this event-related potential (ERP) study, we investigated the effects of format change and semantic relatedness in a recognition task using pairs composed of a word and a line drawing. The semantic relatedness of the pairs (related: rabbit-carrot; unrelated: duck-artichoke) influenced their associative properties and corresponding distinctiveness, while format change refers to the switching of an item from the verbal form to the line drawing form between study and recognition (e.g., the word "egg" is associated with a drawing of a hen at study, and a line drawing of an egg is associated with the word "hen" at test). Study-test format change thus prevents visual matching while maintaining conceptual matching. While the N300 potential was only modulated by the semantic relatedness of the pair, both factors modulated recognition performance and corresponding ERP old/new effects with larger mid-frontal N400 old/new effect (300-500 ms) and larger parietal old/new effect (500-800 ms) in the same compared to the different-format condition, as well as for related compared to unrelated pairs. Furthermore, the semantic relatedness of correctly recognized old pairs modulated the anterior N400 while it modulated the posterior N400 for correctly rejected pairs. These results suggest that semantic relatedness and familiarity related to the amount of change between study and test present distinct ERP signatures in the N400 window. They suggest also that the distinctiveness and the ease of the retrieval of the pair could be determining for the parietal old/new effect.

  11. The effect of semantically related and unrelated vocabularies on EFL learners’ short-term and long term recognition and retention

    Directory of Open Access Journals (Sweden)

    Marzieh Ebrahimi

    2016-10-01

    Full Text Available The present study with a quasi- experimental design, aimed at comparing the effect of semantically related and semantically unrelated clustering on elementary EFL Iranian learner’s recognition ability and their retention. Participants were divided into two groups of 30 learners at elementary level, randomly assigned as experimental and control groups. They were all females, with the age range of 12 to 14, learning English at one of the language Institutes in Mashhad, Iran. Some instruments were used for collecting the research data. The experimental group underwent semantic clustering in which they were provided with eight lists of words, whereas the control group was presented eight unrelated word list with their pictures. An ANCOVA test was used to compare the effectiveness of two groups during short and long period of time. The comparison of two groups in post immediate test have shown that control group outperformed the experimental group, whereas for the delayed test, the results showed a significant difference in favor of semantically related over semantically unrelated clustering. The results have some implications for teaching of foreign language vocabulary instruction.

  12. Toxicology ontology perspectives.

    Science.gov (United States)

    Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic; Cook, David; Dix, Ian; Escher, Sylvia; Hastings, Janna; Heard, David J; Jeliazkova, Nina; Judson, Philip; Matis-Mitchell, Sherri; Mitic, Dragana; Myatt, Glenn; Shah, Imran; Spjuth, Ola; Tcheremenskaia, Olga; Toldo, Luca; Watson, David; White, Andrew; Yang, Chihae

    2012-01-01

    The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

  13. MIMU-Wear: ontology-based sensor selection for real-world wearable activity recognition

    NARCIS (Netherlands)

    Villalonga, Claudia; Pomares, Hector; Rojas, Ignacio; Banos Legran, Oresti

    2017-01-01

    An enormous effort has been made during the recent years towards the recognition of human activity based on wearable sensors. Despite the wide variety of proposed systems, most existing solutions have in common to solely operate on predefined settings and constrained sensor setups. Real-world

  14. ADO: a disease ontology representing the domain knowledge specific to Alzheimer's disease.

    Science.gov (United States)

    Malhotra, Ashutosh; Younesi, Erfan; Gündel, Michaela; Müller, Bernd; Heneka, Michael T; Hofmann-Apitius, Martin

    2014-03-01

    Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases such as Alzheimer's disease, there is a lack of formal representation of the relevant knowledge domain. Alzheimer's disease ontology (ADO) is constructed in accordance to the ontology building life cycle. The Protégé OWL editor was used as a tool for building ADO in Ontology Web Language format. ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references. Validation of the lexicalized ontology by means of named entity recognition-based methods showed a satisfactory performance (F score = 72%). In addition to structural and functional evaluation, a clinical expert in the field performed a manual evaluation and curation of ADO. Through integration of ADO into an information retrieval environment, we show that the ontology supports semantic search in scientific text. The usefulness of ADO is authenticated by dedicated use case scenarios. Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

  15. Cohesion Metrics for Ontology Design and Application

    Directory of Open Access Journals (Sweden)

    Haining Yao

    2005-01-01

    Full Text Available Recently, domain specific ontology development has been driven by research on the Semantic Web. Ontologies have been suggested for use in many application areas targeted by the Semantic Web, such as dynamic web service composition and general web service matching. Fundamental characteristics of these ontologies must be determined in order to effectively make use of them: for example, Sirin, Hendler and Parsia have suggested that determining fundamental characteristics of ontologies is important for dynamic web service composition. Our research examines cohesion metrics for ontologies. The cohesion metrics examine the fundamental quality of cohesion as it relates to ontologies.

  16. 基于兴趣度和本体自适应学习的语义搜索算法研究%ON SEMANTIC SEARCH ALGORITHM BASED ON INTEREST DEGREES AND ONTOLOGY ADAPTIVE LEARNING

    Institute of Scientific and Technical Information of China (English)

    孙萍萍

    2013-01-01

    In order to solve the problems that the users have personal interest preference,the use of ontology effective information is insufficient,the ontology adaptive learning ability is poor and the efficiency of semantic similarity search based on single strategy is low,etc.,we propose a semantic search algorithm which is based on interest degrees and ontology adaptive learning.In this algorithm,firstly,the ontology information sharing content and the closing-to-equilibrium path strategy of information are used to carry out the weighted measurement of ontology semantic similarity,and user' s interest degree preference is calculate as well; Then,according to user personalised preference it carries out the ontology adaptive learning using ontology evaluation model,so as to improve the information sharing degree of ontology knowledge base.Experiment proves that this algorithm has quite high recall and precision rate.%针对用户个人兴趣度偏好、本体有效信息利用不足、本体自适应学习能力差和基于单一策略的语义相似度搜索效率低等问题,提出一种基于兴趣度和本体自适应学习的语义搜索算法.在该算法中,首先利用本体信息共享含量和信息贴近均衡路径策略来进行本体语义相似度加权度量,并对用户的兴趣度进行偏好计算,然后利用本体评价模型,依据用户个性化偏好进行本体自适应学习,从而提高本体知识库的信息共享度.实验证明,该算法具有较高的查全率和查准率.

  17. The facilitation effect of associative and semantic relatedness in word recognition

    Directory of Open Access Journals (Sweden)

    Jakić Milena

    2011-01-01

    Full Text Available In this study we addressed three issues concerning semantic and associative relatedness between two words and how they prime each other. The first issue is whether there is a priming effect of semantic relatedness over and above the effect of associative relatedness. The second issue is how difference in semantic overlap between two words affects priming. In order to specify the semantic overlap we introduce five relation types that differ in number of common semantic components. Three relation types (synonyms, antonyms and hyponyms represent semantic relatedness while two relation types represent associative relatedness, with negligible or no semantic relatedness. Finally, the third issue addressed in this study is whether there is a symmetric priming effect if we swap the position of prime and target, i.e. whether the direction of relatedness between two words affects priming. In two lexical decision experiments we presented five types of word pairs. In both experiments we obtained stronger facilitation for pairs that were both semantically and associatively related. Closer inspection showed that larger semantic overlap between words is paralleled by greater facilitation effect. The effects did not change when prime and target swap their position, indicating that the observed facilitation effects are symmetrical. This outcome complies with predictions of distributed models of memory.

  18. Does N200 reflect semantic processing?--An ERP study on Chinese visual word recognition.

    Science.gov (United States)

    Du, Yingchun; Zhang, Qin; Zhang, John X

    2014-01-01

    Recent event-related potential research has reported a N200 response or a negative deflection peaking around 200 ms following the visual presentation of two-character Chinese words. This N200 shows amplitude enhancement upon immediate repetition and there has been preliminary evidence that it reflects orthographic processing but not semantic processing. The present study tested whether this N200 is indeed unrelated to semantic processing with more sensitive measures, including the use of two tasks engaging semantic processing either implicitly or explicitly and the adoption of a within-trial priming paradigm. In Exp. 1, participants viewed repeated, semantically related and unrelated prime-target word pairs as they performed a lexical decision task judging whether or not each target was a real word. In Exp. 2, participants viewed high-related, low-related and unrelated word pairs as they performed a semantic task judging whether each word pair was related in meaning. In both tasks, semantic priming was found from both the behavioral data and the N400 ERP responses. Critically, while repetition priming elicited a clear and large enhancement on the N200 response, semantic priming did not show any modulation effect on the same response. The results indicate that the N200 repetition enhancement effect cannot be explained with semantic priming and that this specific N200 response is unlikely to reflect semantic processing.

  19. Ontology Mapping for a New Database Integration Model Using an Ontology-driven Mediated Warehousing Approach

    Directory of Open Access Journals (Sweden)

    Ali Ahmed

    2014-04-01

    Full Text Available Ontology mapping is a technique that has become very useful for matching semantics between ontologies or schemas that were designed independently of each other. The main goal of the ontology mapping is to enable interoperability between applications in distributed information systems based on heterogeneous ontologies. To achieve this goal it is necessary to formally define mapping rules between local data sources and ontologies and the notion of a mapping between ontologies. In this study, the authors proposed a new mapping approach, so that the ontologies have to be linked to actual information sources in order to support the integration process. In this approach, first, for each incorporated information source, a local ontology is generated to describe its semantics as well as the resulting mappings between the source and the local ontology, then the local ontologies are mapped to a global ontology using the mapping rule.

  20. simDEF: definition-based semantic similarity measure of gene ontology terms for functional similarity analysis of genes.

    Science.gov (United States)

    Pesaranghader, Ahmad; Matwin, Stan; Sokolova, Marina; Beiko, Robert G

    2016-05-01

    Measures of protein functional similarity are essential tools for function prediction, evaluation of protein-protein interactions (PPIs) and other applications. Several existing methods perform comparisons between proteins based on the semantic similarity of their GO terms; however, these measures are highly sensitive to modifications in the topological structure of GO, tend to be focused on specific analytical tasks and concentrate on the GO terms themselves rather than considering their textual definitions. We introduce simDEF, an efficient method for measuring semantic similarity of GO terms using their GO definitions, which is based on the Gloss Vector measure commonly used in natural language processing. The simDEF approach builds optimized definition vectors for all relevant GO terms, and expresses the similarity of a pair of proteins as the cosine of the angle between their definition vectors. Relative to existing similarity measures, when validated on a yeast reference database, simDEF improves correlation with sequence homology by up to 50%, shows a correlation improvement >4% with gene expression in the biological process hierarchy of GO and increases PPI predictability by > 2.5% in F1 score for molecular function hierarchy. Datasets, results and source code are available at http://kiwi.cs.dal.ca/Software/simDEF CONTACT: ahmad.pgh@dal.ca or beiko@cs.dal.ca Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. 基于本体的科学效应知识表达和语义推理%Scientific effect know ledge representation and semantic reasoning based on ontology

    Institute of Scientific and Technical Information of China (English)

    张星; 马建红; 肖国玺

    2015-01-01

    针对创新设计领域中科学效应知识的表达和语义扩展方面的不足,分析研究效应、功能、流和参数之间的关系和模型,借助本体将概念间属性和关系扩展到语义层次上,通过本体来更加全面地表达科学效应知识,构建科学效应知识本体模型,包括效应本体、功能本体、流本体和参数本体。在此基础上基于属性构建相应的语义推理规则,进行功能扩展和效应关联,通过语义推理实现科学效应知识的共享和重用。开发一个基于本体的科学效应知识检索系统,验证了此模型和方法的有效性和可行性。%Aiming at defects of the scientific effect knowledge expression and semantic extension in innovation design field ,the relations and models of effect ,function ,flow and parameter were analyzed and studied .The concept’s properties and relations between concepts were extended to the semantic level with the help of ontology ,the scientific effect knowledge was expressed more comprehensively through ontology ,and the scientific effect knowledge ontology model was built including effect ontology , function ontology ,flow ontology and parameter ontology .According to the object properties ,reasoning rules were constructed on the basis of scientific effect knowledge ontology model for function extension and effect connection ,and the sharing and appli‐cation of scientific effect knowledge was realized .Finally ,a scientific effect knowledge retrieval system was developed based on ontology to verify the feasibility and the validity of this model and method .

  2. Inhibitory processes and spoken word recognition in young and older adults: the interaction of lexical competition and semantic context.

    Science.gov (United States)

    Sommers, M S; Danielson, S M

    1999-09-01

    Two experiments were conducted to examine the importance of inhibitory abilities and semantic context to spoken word recognition in older and young adults. In Experiment 1, identification scores were obtained in 3 contexts: single words, low-predictability sentences, and high-predictability sentences. Additionally, identification performance was examined as a function of neighborhood density (number of items phonetically similar to a target word). Older adults had greater difficulty than young adults recognizing words with many neighbors (hard words). However, older adults also exhibited greater benefits as a result of adding contextual information. Individual differences in inhibitory abilities contributed significantly to recognition performance for lexically hard words but not for lexically easy words. The roles of inhibitory abilities and linguistic knowledge in explaining age-related impairments in spoken word recognition are discussed.

  3. Using a Foundational Ontology for Reengineering a Software Enterprise Ontology

    Science.gov (United States)

    Perini Barcellos, Monalessa; de Almeida Falbo, Ricardo

    The knowledge about software organizations is considerably relevant to software engineers. The use of a common vocabulary for representing the useful knowledge about software organizations involved in software projects is important for several reasons, such as to support knowledge reuse and to allow communication and interoperability between tools. Domain ontologies can be used to define a common vocabulary for sharing and reuse of knowledge about some domain. Foundational ontologies can be used for evaluating and re-designing domain ontologies, giving to these real-world semantics. This paper presents an evaluating of a Software Enterprise Ontology that was reengineered using the Unified Foundation Ontology (UFO) as basis.

  4. Ontology alignment with OLA

    OpenAIRE

    Euzenat, Jérôme; Loup, David; Touzani, Mohamed; Valtchev, Petko

    2004-01-01

    euzenat2004d; International audience; Using ontologies is the standard way to achieve interoperability of heterogeneous systems within the Semantic web. However, as the ontologies underlying two systems are not necessarily compatible, they may in turn need to be aligned. Similarity-based approaches to alignment seems to be both powerful and flexible enough to match the expressive power of languages like OWL. We present an alignment tool that follows the similarity-based paradigm, called OLA. ...

  5. An Ontology-Based Representation Architecture of Unstructured Information

    Institute of Scientific and Technical Information of China (English)

    GU Jin-guang; CHEN He-ping; CHEN Xin-meng

    2004-01-01

    Integrating with the respective advantages of XML Schema and Ontology, this paper puts forward a semantic information processing architecture-OBSA to solve the problem of heterogeneity of information sources and uncertainty of semantic.It introduces an F-Logic based semantic information presentation mechanism, presents a design of an ontology-based semantic representation language and a mapping algorithm converting Ontology to XML DTD/Schema, and an adapter framework for accessing distributed and heterogeneous information.

  6. SELECTION OF ONTOLOGY FOR WEB SERVICE DESCRIPTION LANGUAGE TO ONTOLOGY WEB LANGUAGE CONVERSION

    Directory of Open Access Journals (Sweden)

    J. Mannar Mannan

    2014-01-01

    Full Text Available Semantic web is to extend the current human readable web to encoding some of the semantic of resources in a machine processing form. As a Semantic web component, Semantic Web Services (SWS uses a mark-up that makes the data into detailed and sophisticated machine readable way. One such language is Ontology Web Language (OWL. Existing conventional web service annotation can be changed to semantic web service by mapping Web Service Description Language (WSDL with the semantic annotation of OWL-S. In this conversion of WSDL to OWL process, the ontology plays a vital role. Ontology can be stored and retrieved from local repository and selecting the appropriate ontology is a complicated process and this can be achieved by Ontology Searching and Property Matching (OSPM engine. Ontology is stored in the local repository as ontology document and exact matching of ontology for the requested query can be searched using semantic similarity ranking method. High ranked classes of ontology will undergo property matching; here requested concept will be matched with the resulting property. OSPM engine act as the backbone for selecting an exact ontology and reduce the conflict that occurs while selecting the ontology for annotation purpose.

  7. Visual Word Recognition: Evidence for Global and Local Control over Semantic Feedback

    Science.gov (United States)

    Robidoux, Serje; Stolz, Jennifer; Besner, Derek

    2010-01-01

    Two lexical decision experiments examined the joint effects of stimulus quality, semantic context, and cue-target associative strength when all factors were intermixed in a block of trials. Both experiments found a three-way interaction. Semantic context and stimulus quality interacted when associative strength between cue-target pairs was strong,…

  8. Ontology or formal ontology

    Science.gov (United States)

    Žáček, Martin

    2017-07-01

    Ontology or formal ontology? Which word is correct? The aim of this article is to introduce correct terms and explain their basis. Ontology describes a particular area of interest (domain) in a formal way - defines the classes of objects that are in that area, and relationships that may exist between them. Meaning of ontology consists mainly in facilitating communication between people, improve collaboration of software systems and in the improvement of systems engineering. Ontology in all these areas offer the possibility of unification of view, maintaining consistency and unambiguity.

  9. Learning expressive ontologies

    CERN Document Server

    Völker, J

    2009-01-01

    This publication advances the state-of-the-art in ontology learning by presenting a set of novel approaches to the semi-automatic acquisition, refinement and evaluation of logically complex axiomatizations. It has been motivated by the fact that the realization of the semantic web envisioned by Tim Berners-Lee is still hampered by the lack of ontological resources, while at the same time more and more applications of semantic technologies emerge from fast-growing areas such as e-business or life sciences. Such knowledge-intensive applications, requiring large scale reasoning over complex domai

  10. Ontology-based application integration

    CERN Document Server

    Paulheim, Heiko

    2011-01-01

    Ontology-based Application Integration introduces UI-level (User Interface Level) application integration and discusses current problems which can be remedied by using ontologies. It shows a novel approach for applying ontologies in system integration. While ontologies have been used for integration of IT systems on the database and on the business logic layer, integration on the user interface layer is a novel field of research. This book also discusses how end users, not only developers, can benefit from semantic technologies. Ontology-based Application Integration presents the development o

  11. Perspectives on ontology learning

    CERN Document Server

    Lehmann, J

    2014-01-01

    Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning.Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the c

  12. A Temporal Web Ontology Language

    NARCIS (Netherlands)

    V. Milea (Viorel); F. Frasincar (Flavius); U. Kaymak (Uzay)

    2009-01-01

    textabstractThe Web Ontology Language (OWL) is the most expressive standard language for modeling ontologies on the Semantic Web. In this paper, we present a temporal extension of the very expressive fragment SHIN(D) of the OWL-DL language resulting in the tOWL language. Through a layered approach w

  13. An examination of semantic radical combinability effects with lateralized cues in Chinese character recognition.

    Science.gov (United States)

    Hsiao, Janet Hui-Wen; Shillcock, Richard; Lavidor, Michal

    2007-04-01

    Auclair and Siéroff examined lateralized cuing effects in the identification of centrally presented letter strings and reported no cuing effects for short word stimuli. They argued for a redistribution of attention over the entire word for short familiar words. We explored cuing effects with Chinese phonetic compounds, which can be considered extreme examples of short words, in a character-level semantic judgment task. When the semantic radical position was placed on the left of the characters, strong radical combinability and semantic transparency effects were observed. There was also a significant interaction between cue position (left vs. right) and radical combinability: A left cue facilitated semantic judgment of characters with small radical combinability more than did a right cue. This behavior reflects the information profile of Chinese phonetic compounds. Semantic radicals with small combinability are more informative than those with large combinability in determining the meaning of the whole character; they therefore benefit more from a left than a right cue. A mechanism redistributing attention over the whole of the character was not in evidence at the level of semantic processing.

  14. Research on Construction of Ontology Services Discovery Oriented in Scientific Workflows (I) --Construction and Architecture of Ontology, Semantic Annotation%面向科学工作流服务发现的本体构建研究(I)——本体构成、框架与语义注释

    Institute of Scientific and Technical Information of China (English)

    李进华; 李璐

    2012-01-01

    科学工作流生命周期由服务组件的发现、解释、组合以及执行等流程组成,其中服务发现是关键。基于本体驱动的服务发现是科学工作流系统的核心功能,包括用于描述服务的本体构建,基于本体的领域/中间服务的语义注释以及基于语义注释的服务查询和组合。本文以生物信息学领域应用为例,阐述了生物信息学本体的功能构成,服务于生物信息学服务发现的领域/服务本体框架结构以及领域/服务本体的语义注释方式和模式。%The life circle of scientific workflows includes services discovery, interpreting, composing and executing, in which service discovery is a key. The discovery of services based on ontology-driven is a kernel function of scientific workflows, which including set up of ontology, semantic annotation of domain/ shim services based ontology and searching and composing of services based on semantic annotation. This article states function of bioinformatics ontology, domain/services ontology's architecture for discovery of bioinformatics services and semantic annotationJs ways and modes, which takes applications in bioinformatics domain for example.

  15. The interaction of lexical semantics and cohort competition in spoken word recognition: an fMRI study.

    Science.gov (United States)

    Zhuang, Jie; Randall, Billi; Stamatakis, Emmanuel A; Marslen-Wilson, William D; Tyler, Lorraine K

    2011-12-01

    Spoken word recognition involves the activation of multiple word candidates on the basis of the initial speech input--the "cohort"--and selection among these competitors. Selection may be driven primarily by bottom-up acoustic-phonetic inputs or it may be modulated by other aspects of lexical representation, such as a word's meaning [Marslen-Wilson, W. D. Functional parallelism in spoken word-recognition. Cognition, 25, 71-102, 1987]. We examined these potential interactions in an fMRI study by presenting participants with words and pseudowords for lexical decision. In a factorial design, we manipulated (a) cohort competition (high/low competitive cohorts which vary the number of competing word candidates) and (b) the word's semantic properties (high/low imageability). A previous behavioral study [Tyler, L. K., Voice, J. K., & Moss, H. E. The interaction of meaning and sound in spoken word recognition. Psychonomic Bulletin & Review, 7, 320-326, 2000] showed that imageability facilitated word recognition but only for words in high competition cohorts. Here we found greater activity in the left inferior frontal gyrus (BA 45, 47) and the right inferior frontal gyrus (BA 47) with increased cohort competition, an imageability effect in the left posterior middle temporal gyrus/angular gyrus (BA 39), and a significant interaction between imageability and cohort competition in the left posterior superior temporal gyrus/middle temporal gyrus (BA 21, 22). In words with high competition cohorts, high imageability words generated stronger activity than low imageability words, indicating a facilitatory role of imageability in a highly competitive cohort context. For words in low competition cohorts, there was no effect of imageability. These results support the behavioral data in showing that selection processes do not rely solely on bottom-up acoustic-phonetic cues but rather that the semantic properties of candidate words facilitate discrimination between competitors.

  16. Ontology for cell-based geographic information

    Science.gov (United States)

    Zheng, Bin; Huang, Lina; Lu, Xinhai

    2009-10-01

    Inter-operability is a key notion in geographic information science (GIS) for the sharing of geographic information (GI). That requires a seamless translation among different information sources. Ontology is enrolled in GI discovery to settle the semantic conflicts for its natural language appearance and logical hierarchy structure, which are considered to be able to provide better context for both human understanding and machine cognition in describing the location and relationships in the geographic world. However, for the current, most studies on field ontology are deduced from philosophical theme and not applicable for the raster expression in GIS-which is a kind of field-like phenomenon but does not physically coincide to the general concept of philosophical field (mostly comes from the physics concepts). That's why we specifically discuss the cell-based GI ontology in this paper. The discussion starts at the investigation of the physical characteristics of cell-based raster GI. Then, a unified cell-based GI ontology framework for the recognition of the raster objects is introduced, from which a conceptual interface for the connection of the human epistemology and the computer world so called "endurant-occurrant window" is developed for the better raster GI discovery and sharing.

  17. Ontological Surprises

    DEFF Research Database (Denmark)

    Leahu, Lucian

    2016-01-01

    This paper investigates how we might rethink design as the technological crafting of human-machine relations in the context of a machine learning technique called neural networks. It analyzes Google’s Inceptionism project, which uses neural networks for image recognition. The surprising output of...... a hybrid approach where machine learning algorithms are used to identify objects as well as connections between them; finally, it argues for remaining open to ontological surprises in machine learning as they may enable the crafting of different relations with and through technologies....

  18. OWL 2 Web Ontology Language: structural specification and functional-style syntax

    NARCIS (Netherlands)

    Motik, B.; Patel-Schneider, P.F.; Parsia, B.; Bock, C.; Fokoue, A.; Haase, P.; Hoekstra, R.; Horrocks, I.; Ruttenberg, A.; Sattler, U.; Smith, M.

    2008-01-01

    The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information writ

  19. OWL 2 Web Ontology Language: structural specification and functional-style syntax

    NARCIS (Netherlands)

    Motik, B.; Patel-Schneider, P.F.; Parsia, B.; Bock, C.; Fokoue, A.; Haase, P.; Hoekstra, R.; Horrocks, I.; Ruttenberg, A.; Sattler, U.; Smith, M.

    2008-01-01

    The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information

  20. Semantic heterogeneity: comparing new semantic web approaches with those of digital libraries

    OpenAIRE

    Krause, Jürgen

    2008-01-01

    To demonstrate that newer developments in the semantic web community, particularly those based on ontologies (simple knowledge organization system and others) mitigate common arguments from the digital library (DL) community against participation in the Semantic web. The approach is a semantic web discussion focusing on the weak structure of the Web and the lack of consideration given to the semantic content during indexing. The points criticised by the semantic web and ontology approaches ar...

  1. Ontology-driven health information systems architectures.

    Science.gov (United States)

    Blobel, Bernd; Oemig, Frank

    2009-01-01

    Following an architecture vision such as the Generic Component Model (GCM) architecture framework, health information systems for supporting personalized care have to be based on a component-oriented architecture. Representing concepts and their interrelations, the GCM perspectives system architecture, domains, and development process can be described by the domains' ontologies. The paper introduces ontology principles, ontology references to the GCM as well as some practical aspects of ontology-driven approaches to semantically interoperable and sustainable health information systems.

  2. The Ontology of Command and Control (C2)

    Science.gov (United States)

    2009-06-01

    semantic uniformity through application of a disciplined approach to ontology. An ontology is a consensus framework representing the types of...Recovery Operation Enforcement of Sanctions Irregular Warfare Peace Making Consequence Mangement Elimination of WMD Peace Enforcement Unconventional Warfare

  3. Semantic Radical Knowledge and Word Recognition in Chinese for Chinese as Foreign Language Learners

    Science.gov (United States)

    Su, Xiaoxiang; Kim, Young-Suk

    2014-01-01

    In the present study, we examined the relation of knowledge of semantic radicals to students' language proficiency and word reading for adult Chinese-as-a-foreign language students. Ninety-seven college students rated their proficiency in speaking, listening, reading, and writing in Chinese, and were administered measures of receptive and…

  4. Feature activation during word recognition: Action, visual, and associative-semantic priming effects

    NARCIS (Netherlands)

    Lam Jia Yoong, K.; Dijkstra, A.F.J.; Rüschemeyer, S.A.

    2015-01-01

    Embodied theories of language postulate that language meaning is stored in modality-specific brain areas generally involved in perception and action in the real world. However, the temporal dynamics of the interaction between modality-specific information and lexical-semantic processing remain

  5. Stereotype Priming in Face Recognition: Interactions between Semantic and Visual Information in Face Encoding

    Science.gov (United States)

    Hills, Peter J.; Lewis, Michael B.; Honey, R. C.

    2008-01-01

    The accuracy with which previously unfamiliar faces are recognised is increased by the presentation of a stereotype-congruent occupation label [Klatzky, R. L., Martin, G. L., & Kane, R. A. (1982a). "Semantic interpretation effects on memory for faces." "Memory & Cognition," 10, 195-206; Klatzky, R. L., Martin, G. L., & Kane, R. A. (1982b).…

  6. The emergence of semantic categorization in early visual processing: ERP indices of animal vs. artifact recognition

    Directory of Open Access Journals (Sweden)

    Del Zotto Marzia

    2007-04-01

    Full Text Available Abstract Background Neuroimaging and neuropsychological literature show functional dissociations in brain activity during processing of stimuli belonging to different semantic categories (e.g., animals, tools, faces, places, but little information is available about the time course of object perceptual categorization. The aim of the study was to provide information about the timing of processing stimuli from different semantic domains, without using verbal or naming paradigms, in order to observe the emergence of non-linguistic conceptual knowledge in the ventral stream visual pathway. Event related potentials (ERPs were recorded in 18 healthy right-handed individuals as they performed a perceptual categorization task on 672 pairs of images of animals and man-made objects (i.e., artifacts. Results Behavioral responses to animal stimuli were ~50 ms faster and more accurate than those to artifacts. At early processing stages (120–180 ms the right occipital-temporal cortex was more activated in response to animals than to artifacts as indexed by posterior N1 response, while frontal/central N1 (130–160 showed the opposite pattern. In the next processing stage (200–260 the response was stronger to artifacts and usable items at anterior temporal sites. The P300 component was smaller, and the central/parietal N400 component was larger to artifacts than to animals. Conclusion The effect of animal and artifact categorization emerged at ~150 ms over the right occipital-temporal area as a stronger response of the ventral stream to animate, homomorphic, entities with faces and legs. The larger frontal/central N1 and the subsequent temporal activation for inanimate objects might reflect the prevalence of a functional rather than perceptual representation of manipulable tools compared to animals. Late ERP effects might reflect semantic integration and cognitive updating processes. Overall, the data are compatible with a modality-specific semantic memory

  7. Image Semantic Automatic Annotation by Relevance Feedback

    Institute of Scientific and Technical Information of China (English)

    ZHANG Tong-zhen; SHEN Rui-min

    2007-01-01

    A large semantic gap exists between content based index retrieval (CBIR) and high-level semantic, additional semantic information should be attached to the images, it refers in three respects including semantic representation model, semantic information building and semantic retrieval techniques. In this paper, we introduce an associated semantic network and an automatic semantic annotation system. In the system, a semantic network model is employed as the semantic representation model, it uses semantic keywords, linguistic ontology and low-level features in semantic similarity calculating. Through several times of users' relevance feedback, semantic network is enriched automatically. To speed up the growth of semantic network and get a balance annotation, semantic seeds and semantic loners are employed especially.

  8. Surreptitious, Evolving and Participative Ontology Development: An End-User Oriented Ontology Development Methodology

    Science.gov (United States)

    Bachore, Zelalem

    2012-01-01

    Ontology not only is considered to be the backbone of the semantic web but also plays a significant role in distributed and heterogeneous information systems. However, ontology still faces limited application and adoption to date. One of the major problems is that prevailing engineering-oriented methodologies for building ontologies do not…

  9. Surreptitious, Evolving and Participative Ontology Development: An End-User Oriented Ontology Development Methodology

    Science.gov (United States)

    Bachore, Zelalem

    2012-01-01

    Ontology not only is considered to be the backbone of the semantic web but also plays a significant role in distributed and heterogeneous information systems. However, ontology still faces limited application and adoption to date. One of the major problems is that prevailing engineering-oriented methodologies for building ontologies do not…

  10. 基于本体概念群组划分的语义距离计算方法%An Ontology Concept-Based Cluster Partition Approach for Computing the Semantic Distance between Concepts

    Institute of Scientific and Technical Information of China (English)

    彭志平; 李晓明; 柯文德

    2011-01-01

    The semantic similarity computing between concepts is an important component in natural language processing etc. , and the semantic similarity computing between concepts based on semantic distance is currently dominant technique. In this paper, the ontology based cluster partition approach for computing the semantic distance between concepts is proposed on the basis of the analysis of the lacks in the existing algorithms. The rules for computing the semantic distance between concepts are given under the situation of multi-concept clusters, and then the approach for computing the semantic distance between concepts within single cluster as well as cross-cluster is put forward. In the proposed approach, the non-symmetry of semantic similarities in the pairs of hyponymy concepts is worked out by introducing the forward semantic distance and the reverse semantic distance, and the other binary relationships of the pairs of non-hyponymy concepts are deal with by dynamically allocating the relation weights in the light of the locations of concept nodes. Experimented results shows that the proposed approach is effective and it is preferable to other typical similar ones.%概念的语义相似度计算是自然语言处理等领域的重要研究内容,基于语义距离的概念相似度计算是其主要方法.在分析现有算法存在弊端的基础上,提出基于领域本体群组划分的概念语义距离计算方法.首先给出多概念群组下概念语义距离的计算规则,然后分别提出群组内和群组间的概念语义距离计算方法,通过引人正向和反向的语义距离来解决上下位关系概念对的语义相似度非对称性,并通过概念节点的位置动态分配关系的权值来处理其他非上下位的二元关系.实验表明,基于领域本体群组划分的概念语义距离计算方法是有效的,与其他典型的同类方法相比,具有明显的优势.

  11. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    We describe principles for extracting information from texts using a so-called generative ontology in combination with syntactic analysis. Generative ontologies are introduced as semantic domains for natural language phrases. Generative ontologies extend ordinary finite ontologies with rules...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....... for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...

  12. Native-Language Phonological Interference in Early Hakka-Mandarin Bilinguals' Visual Recognition of Chinese Two-Character Compounds: Evidence from the Semantic-Relatedness Decision Task

    Science.gov (United States)

    Wu, Shiyu; Ma, Zheng

    2017-01-01

    Previous research has indicated that, in viewing a visual word, the activated phonological representation in turn activates its homophone, causing semantic interference. Using this mechanism of phonological mediation, this study investigated native-language phonological interference in visual recognition of Chinese two-character compounds by early…

  13. Native-Language Phonological Interference in Early Hakka-Mandarin Bilinguals' Visual Recognition of Chinese Two-Character Compounds: Evidence from the Semantic-Relatedness Decision Task

    Science.gov (United States)

    Wu, Shiyu; Ma, Zheng

    2017-01-01

    Previous research has indicated that, in viewing a visual word, the activated phonological representation in turn activates its homophone, causing semantic interference. Using this mechanism of phonological mediation, this study investigated native-language phonological interference in visual recognition of Chinese two-character compounds by early…

  14. 基于本体分类结构计算医疗领域语义相似度的方法%Semantic Similarity Measures Based on Ontology Hierarchy Structure in Biomedical Domain

    Institute of Scientific and Technical Information of China (English)

    张莹

    2013-01-01

    相似度计算能提高从医疗源数据进行信息检索的效率并使得异构临床数据的集成变得更加容易。不同学者基于单个医疗本体,将经典的相似度计算方法用于医疗术语的相似性评估。本文选定基于距离的LCH方法,依据Pederson基准,对比该算法在基于MeSH、SNOMEDCT、UMLS本体时的相关度值,并就计算结果进行分析和解释。%Semantic similarity computation can promote the efficiency of information retrieval of biomedical resources, and make the integration of heterogeneous clinical data more easier. Various experts devote themselves on the application of classic semantic similarity measures over single biomedical ontology and develop them. In this paper, we compare the results for LCH measure over various ontologies such as MeSH SNOMED CT and UMLS. Finally we analysis and explain the results.

  15. OBIB-a novel ontology for biobanking.

    Science.gov (United States)

    Brochhausen, Mathias; Zheng, Jie; Birtwell, David; Williams, Heather; Masci, Anna Maria; Ellis, Helena Judge; Stoeckert, Christian J

    2016-01-01

    Biobanking necessitates extensive integration of data to allow data analysis and specimen sharing. Ontologies have been demonstrated to be a promising approach in fostering better semantic integration of biobank-related data. Hitherto no ontology provided the coverage needed to capture a broad spectrum of biobank user scenarios. Based in the principles laid out by the Open Biological and Biomedical Ontologies Foundry two biobanking ontologies have been developed. These two ontologies were merged using a modular approach consistent with the initial development principles. The merging was facilitated by the fact that both ontologies use the same Upper Ontology and re-use classes from a similar set of pre-existing ontologies. Based on the two previous ontologies the Ontology for Biobanking (http://purl.obolibrary.org/obo/obib.owl) was created. Due to the fact that there was no overlap between the two source ontologies the coverage of the resulting ontology is significantly larger than of the two source ontologies. The ontology is successfully used in managing biobank information of the Penn Medicine BioBank. Sharing development principles and Upper Ontologies facilitates subsequent merging of ontologies to achieve a broader coverage.

  16. An Ontology-based Time Semantic Specification and Verification Approach for Web Service%一种基于Ontology的WEB服务时间约束定义及验证方法

    Institute of Scientific and Technical Information of China (English)

    刘如娟; 陈俊杰; 王立军; 谢红薇

    2009-01-01

    To solve the problem that Non-functional property specification & verification in web service (WS) flow has become indispensable, an ontology-based approach was presented for specifying and verifying time constraints consistency in WS flow. Time OWL-S was built to express basic time information of WS flow roundly. Meanwhile, Petri Nets Ontology was enriched with time semantic information, which can describe WS semantics based on OWL. The mapping definition between Time OWL-S and extended Petfi Nets Ontology was also given. Through extending OWL-S API,annotated OWL-S model was transformed into PNML, a standard format to describe Petri Nets Ontolo-gy. A verification system was taken to illustrate the correctness and feasibility of the verification process.%针对目前面向服务计算(SCO)模式中组合Web服务验证缺乏对时间等非功能属性验证的实际,基于本体理论,设计并实现了一种基于时间约束Petri网的Web服务时间模型定义方法.该方法考虑服务流与以往工作流的区别,在服务模型OWL-S基础上建立时间本体(Time Ontology),全面地刻画了服务的基本时间约束.扩展已有的PetIi网本体,增强其描述能力,使其能够描述服务数据及时间信息,并定义了在OWL-S上定义的时间本体与Pe-tri网时间本体间的关系.根据模型检测理论,通过扩展OWL-API,将附加时间属性的OWL-S的服务描述本体转换为Petri网的标准格式PNML文件,建立起扩展时间属性的Web服务模型与形式化模型时间约束PetIi网(TCPN)间的映射关系.该方法很好地描述了服务时间约束,为后续的基于TCPN的服务时间形式化验证打下了坚定的基础.

  17. Building Ontologies to Understand Spoken Tunisian Dialect

    CERN Document Server

    Graja, Marwa; Belguith, Lamia Hadrich

    2011-01-01

    This paper presents a method to understand spoken Tunisian dialect based on lexical semantic. This method takes into account the specificity of the Tunisian dialect which has no linguistic processing tools. This method is ontology-based which allows exploiting the ontological concepts for semantic annotation and ontological relations for speech interpretation. This combination increases the rate of comprehension and limits the dependence on linguistic resources. This paper also details the process of building the ontology used for annotation and interpretation of Tunisian dialect in the context of speech understanding in dialogue systems for restricted domain.

  18. A Formal Theory for Modular ERDF Ontologies

    Science.gov (United States)

    Analyti, Anastasia; Antoniou, Grigoris; Damásio, Carlos Viegas

    The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.

  19. Introduction to geospatial semantics and technology workshop handbook

    Science.gov (United States)

    Varanka, Dalia E.

    2012-01-01

    The workshop is a tutorial on introductory geospatial semantics with hands-on exercises using standard Web browsers. The workshop is divided into two sections, general semantics on the Web and specific examples of geospatial semantics using data from The National Map of the U.S. Geological Survey and the Open Ontology Repository. The general semantics section includes information and access to publicly available semantic archives. The specific session includes information on geospatial semantics with access to semantically enhanced data for hydrography, transportation, boundaries, and names. The Open Ontology Repository offers open-source ontologies for public use.

  20. Health care ontologies: knowledge models for record sharing and decision support.

    Science.gov (United States)

    Madsen, Maria

    2010-01-01

    This chapter gives an educational overview of: * The difference between informal and formal ontologies * The primary objectives of ontology design, re-use, extensibility, and interoperability * How formal ontologies can be used to map terminologies and classification systems * How formal ontologies improve semantic interoperability * The relationship between a well-formed ontology and the development of intelligent decision support.

  1. Semantic SenseLab: Implementing the vision of the Semantic Web in neuroscience.

    Science.gov (United States)

    Samwald, Matthias; Chen, Huajun; Ruttenberg, Alan; Lim, Ernest; Marenco, Luis; Miller, Perry; Shepherd, Gordon; Cheung, Kei-Hoi

    2010-01-01

    Integrative neuroscience research needs a scalable informatics framework that enables semantic integration of diverse types of neuroscience data. This paper describes the use of the Web Ontology Language (OWL) and other Semantic Web technologies for the representation and integration of molecular-level data provided by several of SenseLab suite of neuroscience databases. Based on the original database structure, we semi-automatically translated the databases into OWL ontologies with manual addition of semantic enrichment. The SenseLab ontologies are extensively linked to other biomedical Semantic Web resources, including the Subcellular Anatomy Ontology, Brain Architecture Management System, the Gene Ontology, BIRNLex and UniProt. The SenseLab ontologies have also been mapped to the Basic Formal Ontology and Relation Ontology, which helps ease interoperability with many other existing and future biomedical ontologies for the Semantic Web. In addition, approaches to representing contradictory research statements are described. The SenseLab ontologies are designed for use on the Semantic Web that enables their integration into a growing collection of biomedical information resources. We demonstrate that our approach can yield significant potential benefits and that the Semantic Web is rapidly becoming mature enough to realize its anticipated promises. The ontologies are available online at http://neuroweb.med.yale.edu/senselab/. 2009 Elsevier B.V. All rights reserved.

  2. Application of the Financial Industry Business Ontology (FIBO) for development of a financial organization ontology

    Science.gov (United States)

    Petrova, G. G.; Tuzovsky, A. F.; Aksenova, N. V.

    2017-01-01

    The article considers an approach to a formalized description and meaning harmonization for financial terms and means of semantic modeling. Ontologies for the semantic models are described with the help of special languages developed for the Semantic Web. Results of FIBO application to solution of different tasks in the Russian financial sector are given.

  3. Ontology modeling for generation of clinical pathways

    Directory of Open Access Journals (Sweden)

    Jasmine Tehrani

    2012-12-01

    Full Text Available Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the

  4. Emotional valence and semantic relatedness differentially influence false recognition in mild cognitive impairment, Alzheimer's disease, and healthy elderly.

    Science.gov (United States)

    Brueckner, Katja; Moritz, Steffen

    2009-03-01

    This study examined whether patients with mild cognitive impairment (MCI) who are at higher risk for later Alzheimer disease (AD) display deficits comparable to patients with diagnosed dementia. We assessed 27 patients with MCI, 36 patients with AD, and 20 healthy older adults with an emotional variant of the Deese-Roediger-McDermott-paradigm. Participants studied four lists that were semantically related to a nonpresented critical theme word. These theme words were either depression-related (i.e., loneliness) or delusion-related (betrayal) or had a positive (holidays) or neutral (window) valence. Despite a normal overall emotional memory and a normal corrected overall false recognition, patients with MCI, as predicted, produced as many false memories as patients with AD. On closer examination, both patient groups showed enhanced false memories to unrelated stimuli and a significant bias to falsely remember stimuli with a positive valence. We conclude that although patients with MCI are not distinguishable from healthy older adults in terms of their overall emotional recognition, positively valenced memories and more specifically false positive memories may represent the signature of a breakdown of emotional memory along the continuum between normal aging and AD.

  5. Recognition of the semantics and kinematics of gestures: Neural responses to "what" and "how"?

    Science.gov (United States)

    Dahan, Anat; Reiner, Miriam

    2016-10-15

    The extensive use of gestures for human-human communication, independently of culture and language, suggests an underlying universal neural mechanism for gesture recognition. The mirror neuron system (MNS) is known to respond to observed human actions, and overlaps with self-action. The minimal cues needed for activation of the MNS for gesture recognition, facial expressions and bodily dynamics, is not yet defined. Using LED-point representations of gestures, we compared two types of brain activations: 1) in response to human recognizable vs non-recognizable motion and 2) in response to human vs non-human motion. Our preliminary results show that parts of the MNS respond only to human kinematics, and not to nonhuman kinematics, suggesting that the brain has a mechanism of discriminating human from nonhuman motion, even if the pattern of motion is meaningless, but still follows biological motion patterns. This implies that mechanisms of learning-mimicking, empathy and emotional communication, are possibly constrained by biological motion patterns. We then suggest a two-tier-model of human-bodily-communication: (1) recognition of human biological kinematics; (2) recognition of meaning. Implications are both theoretical (understanding the underlying mechanism for action recognition) and applicative (in digital graphical social representations, motion should be reasonably biological to generate the same emotional and mimicking automatic mechanisms as in face-to-face social interactions).

  6. Order Theoretical Semantic Recommendation

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, Cliff A.; Hogan, Emilie A.; Paulson, Patrick R.; Peterson, Elena S.; Stephan, Eric G.; Thomas, Dennis G.

    2013-07-23

    Mathematical concepts of order and ordering relations play multiple roles in semantic technologies. Discrete totally ordered data characterize both input streams and top-k rank-ordered recommendations and query output, while temporal attributes establish numerical total orders, either over time points or in the more complex case of startend temporal intervals. But also of note are the fully partially ordered data, including both lattices and non-lattices, which actually dominate the semantic strcuture of ontological systems. Scalar semantic similarities over partially-ordered semantic data are traditionally used to return rank-ordered recommendations, but these require complementation with true metrics available over partially ordered sets. In this paper we report on our work in the foundations of partial order measurement in ontologies, with application to top-k semantic recommendation in workflows.

  7. 基于语义本体的柑橘肥水管理决策支持系统%A decision support system for fertilization and irrigation management of citrus based on semantic ontology

    Institute of Scientific and Technical Information of China (English)

    王艺; 王英; 原野; 郭云龙; 张自力; 邓烈; 李莉

    2014-01-01

    The key problems for realizing precision agriculture include integrating heterogeneous and multi-source agricultural information, developing localization agricultural resources, and providing personalized and active information services for individual farmers. In this paper, we present an approach to precision farming in citrus production management by using semantic technology. In our work, the first step was to transfer the expert knowledge existing in technical reports and books into the citrus fertilization and irrigation ontology that could be understood and directly computed by computer systems. By developing the ontology based on the semantic technology such as the resource framework description triples graph, heterogeneous and multi-source information was integrated into computable localization resources. We described how knowledge in the form of texts, pictures, and tables were encoded into resource description framework triples respectively. In addition, we also discussed how to establish properties, which is a difficulty in ontology development. Our ontology development process was supported by a set of professional tools:TopBraid Composer, the world’s most powerful modeling environment, and Gruff, a graphical triple-store browser. We created 31 properties in total and used another five standard properties from the Semantic Web standards. As our aim for building the ontology was to support the decision making for citrus production management, our citrus ontology was not just taxonomy for the citrus management knowledge compared to the existing agricultural ontologies. Then we developed a personalized decision support system for citrus fertilization and irrigation management, based on the ontology. Different from the existing agricultural information services, our system can actively provide personalized production management instructions for individual farmers via multiple terminal devices, including mobile phones and Web browsers. The demo application

  8. ENRICHMENT OF OBO ONTOLOGIES

    Science.gov (United States)

    Bada, Michael; Hunter, Lawrence

    2006-01-01

    This paper describes a frame-based integration of the three GO subontologies, the Chemicals of Biological Interest ontology (ChEBI), and the Cell Type Ontology (CTO) in which relationships between elements of the ontologies are modeled in a way that better captures the relational semantics between biological concepts represented by the terms, rather than between the terms themselves, than previous frame-based efforts. We also describe a methodology for creating suggested enriching assertions of the form (subject, relationship, object) by identifying patterns in GO terms, mapping these patterns and subpatterns to relationships, matching concepts to these patterns and subpatterns, and integrating these assertions into the ontologies. Using this methodology, a large number of reliable assertions linking previously unlinked OBO terms using a wide variety of specific, hierarchically arranged relationships were created: A predicted assertion was made for 62% of GO terms that matched one of 31 patterns, and 97% of these predicted assertions were assessed to be valid; a further 429 assertions (corresponding to 6% of the matching terms) were manually created, resulting in an initial set of 4,497 assertions. Furthermore, this methodology programmatically integrates assertions into a base ontology such that each assertion is fully consistent with respect to higher (i.e., more general) relevant class and slot levels. Such an integration is absent from previous compositional efforts, and we argue its necessity for the creation of coherent biological ontologies when linking previously unlinked terms. PMID:17011833

  9. 语义类标记在中国手语词词汇识别和语义提取中的作用%The Effect of Semantic Classifier on Lexical Recognition and Semantic Extraction of Chinese Sign Language

    Institute of Scientific and Technical Information of China (English)

    陈穗清; 张积家; 吴雪云; 高珂娟

    2012-01-01

    通过2个实验,考察了语义类标记在中国手语词汇识别和语义提取中的作用.实验1采用手语词汇判断任务,比较了有、无语义类标记的手语词汇识别.实验2采用语义决定任务,探讨了语义类标记对手语词语义提取的影响.结果表明,语义类标记影响聋生对手语词的识别和语义提取.聋生识别有语义类标记的手语词显著快于识别无语义类标记的手语词.当语义类标记与手语词的语义一致时,能够促进聋生对手语词的语义提取;当语义类标记与手语词的语义不一致,会干扰聋生对手语词的语义提取.中国手语词语义类标记效应的发现,丰富了中国手语词词汇认知的理论,,对聋人的语言教学和概念教学具有重要的启示.%Classifier is a symbol of an object belonging to a particular class. Sign language classifier is a kind of hand-shape which included location, shape, movement and orientation, or with a particular non-manual feature. As one of major factors in sign language, however, the semantic classifier construction in Chinese Sign Language (CSL) has seldom been investigated as a special field. Likewise, YiFu (shapes) of Chinese characters signifies their meaning directly and YiFu is the main carriers of this function. Many studies have examined the role of components in the recognition of Chinese characters. The results showed that the effect of YiFu existed in semantic processing of Chinese words. In addition, by means of word classifying, the studies showed that the symbol of the upper concepts in concept names played an important role in the semantic extraction of scientific and natural concepts. According to the results of the study of Chinese characters, the semantic classifier might affect the recognition of sign language. As a result, we adopted three semantic categories to examine how the semantic classifier of sign language affect the deaf in recognition of the sign language. The three

  10. 基于本体的新疆兵团空间数据语义描述及其应用与评估%Ontology-Based Semantic Description of Spatial Data

    Institute of Scientific and Technical Information of China (English)

    李伟; 赵庆展; 韩峰

    2012-01-01

    为了解决兵团空间信息集成与数据共享的问题,本文在兵团空间信息建设现状和空间数据认知过程分析的基础上,采用空间数据本体的方法研究兵团空间数据的认知表达,并由此提出基于地理本体的兵团空间数据含义和概念框架,建立了能客观反映兵团空间实体的描述逻辑和知识表达方式.最后,在本体构建,概念类型、语义关系研究基础上对空间数据本体进行语义描述应用并予以评估.结果表明,本文利用地理本体思想对兵团空间数据进行的语义描述有效.有利于兵团空间数据共享和集成.%To solve the problem of spatial information integration and data sharing in Xinjiang Production and Construction Corps. Based on the current state of the spatial information construction of the Corps and the analysis of the cognitive process, this paper studied the cognitive expression of the Corps spatial data by using ontology, proposed the meaning and conceptual framework of the Corps spatial data based on the geographical ontology,and established a descriptive logic and knowledge representation methods which could objectively reflect the Corps spatial entity. Based on ontology construction,conceptual types and semantic relationships, this paper described and applied the spatial data of the Corps and made assessment. The results show that,the use of Geographic Ontology thinking on semantic description of spatial data is effective,and it is beneficial to the spatial information integration and data sharing in the Corps.

  11. Multimedia ontology representation and applications

    CERN Document Server

    Chaudhury, Santanu; Ghosh, Hiranmay

    2015-01-01

    The result of more than 15 years of collective research, Multimedia Ontology: Representation and Applications provides a theoretical foundation for understanding the nature of media data and the principles involved in its interpretation. The book presents a unified approach to recent advances in multimedia and explains how a multimedia ontology can fill the semantic gap between concepts and the media world. It relays real-life examples of implementations in different domains to illustrate how this gap can be filled.The book contains information that helps with building semantic, content-based

  12. The ontology-based answers (OBA) service: a connector for embedded usage of ontologies in applications.

    Science.gov (United States)

    Dönitz, Jürgen; Wingender, Edgar

    2012-01-01

    The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and "partOf" relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba.

  13. Ontology of the False State

    Directory of Open Access Journals (Sweden)

    Testa Italo

    2015-09-01

    Full Text Available In this paper I will argue that critical theory needs to make its socio-ontological commitments explicit, whilst on the other hand I will posit that contemporary social ontology needs to amend its formalistic approach by embodying a critical theory perspective. In the first part of my paper I will discuss how the question was posed in Horkheimer’s essays of the 1930s, which leave open two options: (1 a constructive inclusion of social ontology within social philosophy, or else (2 a program of social philosophy that excludes social ontology. Option (2 corresponds to Adorno’s position, which I argue is forced to recur to a hidden social ontology. Following option (1, I first develop a meta-critical analysis of Searle, arguing that his social ontology presupposes a notion of ‘recognition’ which it cannot account for. Furthermore, by means of a critical reading of Honneth, I argue that critical theory could incorporate a socio-ontological approach, giving value to the constitutive socio-ontological role of recognition and to the socio-ontological role of objectification. I will finish with a proposal for a socio-ontological characterization of reification which involves that the basic occurrence of recognition is to be grasped at the level of background practices.

  14. WEB MINING BASED FRAMEWORK FOR ONTOLOGY LEARNING

    OpenAIRE

    Ramesh, C.; K.V.Chalapati Rao; Govardhan, A

    2015-01-01

    Today, the notion of Semantic Web has emerged as a prominent solution to the problem of organizing the immense information provided by World Wide Web, and its focus on supporting a better co-operation between humans and machines is noteworthy. Ontology forms the major component of Semantic Web in its realization. However, manual method of ontology construction is time-consuming, costly, error-prone and inflexible to change and in addition, it requires a complete participation o...

  15. Context Ontology Implementation for Smart Home

    CERN Document Server

    Van Nguyen, Tam; Nguyen, Huy; Choi, Deokjai; Lee, Chilwoo

    2010-01-01

    Context awareness is one of the important fields in ubiquitous computing. Smart Home, a specific instance of ubiquitous computing, provides every family with opportunities to enjoy the power of hi-tech home living. Discovering that relationship among user, activity and context data in home environment is semantic, therefore, we apply ontology to model these relationships and then reason them as the semantic information. In this paper, we present the realization of smart home's context-aware system based on ontology. We discuss the current challenges in realizing the ontology context base. These challenges can be listed as collecting context information from heterogeneous sources, such as devices, agents, sensors into ontology, ontology management, ontology querying, and the issue related to environment database explosion.

  16. Logical Characterisation of Ontology Construction using Fuzzy Description Logics

    DEFF Research Database (Denmark)

    Badie, Farshad; Götzsche, Hans

    Ontologies based on Description Logics (DLs) have proved to be effective in formally sharing knowledge across semantic technologies, e.g. Semantic Web, Natural Language Processing, Text Analytics, Business intelligence. Our main goal is analysing ontology construction considering vagueness. We have...

  17. An ontology framework for quality of geographic information services

    NARCIS (Netherlands)

    Onchaga, R.; Widya, I.A.; Morales Guarin, J.M.; Nieuwenhuis, Lambertus Johannes Maria; Aref, W.G.; Mokbel, F.; Samet, H.; Schneider, M.; Shahabi, C.; Wolfson, O.

    2008-01-01

    In recent years, there has been much research on ontologies for geographic information (GI) services. But to date, focus has been on semantics of data and operations. Much less attention has been given to semantics of quality of GI services. In addressing this gap, this paper proposes an ontology

  18. Data Migration for Ontology Evolution

    Institute of Scientific and Technical Information of China (English)

    赵彦; 张雷; 林晨曦; 张卓; 俞勇

    2004-01-01

    Ontology is the conceptual backbone that provides meaning to data on the semantic web. However, ontology is not a static resource and may evolve over time, which often leaves the meaning of data in an undefined or inconsistent state. It is thus very important to have a method to preserve the data and its meaning when ontology changes. This paper proposed a general method that solves the problem using data migration. It analyzed some of the issues in the method including separation of ontology and data, migration specification, migration result and migration algorithm. The paper also instantiates the general mothod in RDF(S) as an example. The RDF(S) example itself is a simple but complete method for migrating RDF data when RDFS ontology changes.

  19. The interaction of lexical tone, intonation and semantic context in on-line spoken word recognition: an ERP study on Cantonese Chinese.

    Science.gov (United States)

    Kung, Carmen; Chwilla, Dorothee J; Schriefers, Herbert

    2014-01-01

    In two ERP experiments, we investigate the on-line interplay of lexical tone, intonation and semantic context during spoken word recognition in Cantonese Chinese. Experiment 1 shows that lexical tone and intonation interact immediately. Words with a low lexical tone at the end of questions (with a rising question intonation) lead to a processing conflict. This is reflected in a low accuracy in lexical identification and in a P600 effect compared to the same words at the end of a statement. Experiment 2 shows that a strongly biasing semantic context leads to much better lexical-identification performance for words with a low tone at the end of questions and to a disappearance of the P600 effect. These results support the claim that semantic context plays a major role in disentangling the tonal information from the intonational information, and thus, in resolving the on-line conflict between intonation and tone. However, the ERP data indicate that the introduction of a semantic context does not entirely eliminate on-line processing problems for words at the end of questions. This is revealed by the presence of an N400 effect for words with a low lexical tone and for words with a high-mid lexical tone at the end of questions. The ERP data thus show that, while semantic context helps in the eventual lexical identification, it makes the deviation of the contextually expected lexical tone from the actual acoustic signal more salient. © 2013 Published by Elsevier Ltd.

  20. An ontology roadmap for crowdsourcing innovation intermediaries

    OpenAIRE

    Silva, Cândida; Ramos, Isabel

    2014-01-01

    Ontologies have proliferated in the last years, essentially justified by the need of achieving a consensus in the multiple representations of reality inside computers, and therefore the accomplishment of interoperability between machines and systems. Ontologies provide an explicit conceptualization that describes the semantics of the data. Crowdsourcing innovation intermediaries are organizations that mediate the communication and relationship between companies that aspire to solv...

  1. The Knowledge Base Based on Ontology Semantic WEB Expanded Search Method%基于本体的知识库语义WEB扩展搜索方法研究

    Institute of Scientific and Technical Information of China (English)

    袁辉; 李延香

    2013-01-01

    As the foundation of knowledge management, the function of knowledge base is very important. Based on the reasoning and keyword matching combination of search method is the search for knowledge base of the commonly used method, but by the user expression is not clear, the term lack, etc., influenced the retrieval efficiency, and is not very good, people to the knowledge base of information retrieval needs can't all come true. By introducing the semantic web ontology technology and query expansion technology can greatly improve the efficiency of retrieval, satisfy people's demand information retrieval. In this paper, the knowledge base based on ontology semantic WEB expanded search methods are discussed and research.%  作为知识管理的基础,知识库的作用十分重要。基于推理和关键字匹配相结合的搜索方法是目前对知识库进行搜索的常用方法,不过受用户表达不清楚、检索词匮乏等方面影响,检索效率并不是很好,人们对知识库信息检索的各种需求无法全部实现。通过引入语义网本体技术与查询扩展技术能够大幅提升检索效率,满足人们的信息检索需求。本文对基于本体的知识库语义WEB扩展搜索方法进行了探讨和研究。

  2. Performing ontology.

    Science.gov (United States)

    Aspers, Patrik

    2015-06-01

    Ontology, and in particular, the so-called ontological turn, is the topic of a recent themed issue of Social Studies of Science (Volume 43, Issue 3, 2013). Ontology, or metaphysics, is in philosophy concerned with what there is, how it is, and forms of being. But to what is the science and technology studies researcher turning when he or she talks of ontology? It is argued that it is unclear what is gained by arguing that ontology also refers to constructed elements. The 'ontological turn' comes with the risk of creating a pseudo-debate or pseudo-activity, in which energy is used for no end, at the expense of empirical studies. This text rebuts the idea of an ontological turn as foreshadowed in the texts of the themed issue. It argues that there is no fundamental qualitative difference between the ontological turn and what we know as constructivism.

  3. On the Application of Semantic Web Ontology in Discrete Mathematics Teaching%语义网本体在离散数学课程教学中的应用

    Institute of Scientific and Technical Information of China (English)

    康达周

    2014-01-01

    The Semantic Web and ontology technologies have been widely applied in knowledge engineering, artificial intelli-gence and computer science, and also play an important role in education and research areas. The present discrete mathematics courses are facing difficulties with wide content, various concepts, highly abstract and theoretical. This paper proposes to use ontol-ogy as an important tool in teaching discrete mathematics to help students understand, apply and practice knowledge in discrete mathematics. It presents the roles, ideas and methods of using ontology in different stages of teaching process, and shows the teaching effectiveness and feedback from students.%语义网本体广泛应用于知识工程、人工智能以及计算机科学领域,在教育、科研等方面也有重要作用。针对当前离散数学课程教学中存在的内容广、概念多、高度抽象和理论化等困难,利用本体作为辅助离散数学课程教学的重要工具,辅助学生理解、应用和实践离散数学知识,提出本体在教学过程中不同方面所起的作用以及教学思路与方法,得到了很好的教学效果和学生反馈。

  4. Semantic Session Analysis for Web Usage Mining

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hui; SONG Hantao; XU Xiaomei

    2007-01-01

    A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is used to identifying which active session a request should belong to. The competitive method is applied to determine the end of the sessions.Compared with other algorithms, more successful sessions are additionally detected by semantic outlier analysis.

  5. Towards semantic software engineering enviroments

    NARCIS (Netherlands)

    Falbo, R.A.; Guizzardi, G.; Natali, A.; Bertollo, G.; Ruy, F.; Mian, P.; Tortora, G.; Chang, S.K.

    2002-01-01

    Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they are a way towards Semantic SEEs. In this paper we discuss an ontology-based

  6. Towards semantic software engineering environments

    NARCIS (Netherlands)

    Falbo, R.A.; Guizzardi, G.; Natali, A.; Bertollo, G.; Ruy, F.; Mian, P.; Tortora, G.; Chang, S.-K.

    2002-01-01

    Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they are a way towards Semantic SEEs. In this paper we discuss an ontology-based appr

  7. Towards semantic software engineering enviroments

    NARCIS (Netherlands)

    Falbo, R.A.; Guizzardi, G.; Natali, A.; Bertollo, G.; Ruy, F.; Mian, P.; Tortora, G.; Chang, S.K.

    2002-01-01

    Software tools processing partially common set of data should share an understanding of what these data mean. Since ontologies have been used to express formally a shared understanding of information, we argue that they are a way towards Semantic SEEs. In this paper we discuss an ontology-based appr

  8. Rules-based object-relational databases ontology construction

    Institute of Scientific and Technical Information of China (English)

    Chen Jia; Wu Yue

    2009-01-01

    To solve the problems of sharing and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions axe formalized affording to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.

  9. ONTOGRABBING: Extracting Information from Texts Using Generative Ontologies

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer; Szymczak, Bartlomiej Antoni; Jensen, P.A.

    2009-01-01

    for producing recursively shaped terms representing the ontological content (ontological semantics) of NL noun phrases and other phrases. We focus here on achieving a robust, often only partial, ontology-driven parsing of and ascription of semantics to a sentence in the text corpus. The aim of the ontological...... analysis is primarily to identify paraphrases, thereby achieving a search functionality beyond mere keyword search with synsets. We further envisage use of the generative ontology as a phrase-based rather than word-based browser into text corpora....

  10. Interoperability for Global Observation Data by Ontological Information

    Institute of Scientific and Technical Information of China (English)

    Masahiko Nagai; Masafumi Ono; Ryosuke Shibasaki

    2008-01-01

    The Ontology registry system is developed to collect, manage, and compare ontological informa-tion for integrating global observation data. Data sharing and data service such as support of metadata deign, structudng of data contents, support of text mining are applied for better use of data as data interop-erability. Semantic network dictionary and gazetteers are constructed as a trans-disciplinary dictionary. On-tological information is added to the system by digitalizing text based dictionaries, developing "knowledge writing tool" for experts, and extracting semantic relations from authodtative documents with natural lan-guage processing technique. The system is developed to collect lexicographic ontology and geographic ontology.

  11. An information retrieval approach to ontology mapping

    NARCIS (Netherlands)

    Su, X.; Gulla, J.A.

    2006-01-01

    In this paper, we present a heuristic mapping method and a prototype mapping system that support the process of semi-automatic ontology mapping for the purpose of improving semantic interoperability in heterogeneous systems. The approach is based on the idea of semantic enrichment, i.e., using insta

  12. Semantic contribution to verbal short-term memory: are pleasant words easier to remember than neutral words in serial recall and serial recognition?

    Science.gov (United States)

    Monnier, Catherine; Syssau, Arielle

    2008-01-01

    In the four experiments reported here, we examined the role of word pleasantness on immediate serial recall and immediate serial recognition. In Experiment 1, we compared verbal serial recall of pleasant and neutral words, using a limited set of items. In Experiment 2, we replicated Experiment 1 with an open set of words (i.e., new items were used on every trial). In Experiments 3 and 4, we assessed immediate serial recognition of pleasant and neutral words, using item sets from Experiments 1 and 2. Pleasantness was found to have a facilitation effect on both immediate serial recall and immediate serial recognition. This study supplies some new supporting arguments in favor of a semantic contribution to verbal short-term memory performance. The pleasantness effect observed in immediate serial recognition showed that, contrary to a number of earlier findings, performance on this task can also turn out to be dependent on semantic factors. The results are discussed in relation to nonlinguistic and psycholinguistic models of short-term memory.

  13. 一种基于Ontology的异构数据库语义集成方法%An Ontology-Based Approach to Heterogeneous Database Semantic Integration

    Institute of Scientific and Technical Information of China (English)

    吴玲丽; 余建桥; 孙荣荣

    2008-01-01

    随着数据的大量增加,数据之间的结构异构和语义异构成为数据集成的重点与难点.本文利用 Ontolo-gy 语义集成上的优点,提出了一种基于 Ontology 的异构数据库的语义集成框架,并提出采用基于概念名称语义相似性、属性类型相似度和实例相似度的语义映射方法来重点解决语义集成中的映射问题.

  14. Impact of ontology evolution on functional analyses.

    Science.gov (United States)

    Groß, Anika; Hartung, Michael; Prüfer, Kay; Kelso, Janet; Rahm, Erhard

    2012-10-15

    Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes. Our results show that past changes in the GO are non-uniformly distributed over different branches of the ontology. Considering the semantic relatedness of significant categories in analysis results allows a more realistic stability assessment for functional enrichment studies. We observe that the results of term-enrichment analyses tend to be surprisingly stable despite changes in ontology and annotation.

  15. WEB MINING BASED FRAMEWORK FOR ONTOLOGY LEARNING

    Directory of Open Access Journals (Sweden)

    C.Ramesh

    2015-07-01

    Full Text Available Today, the notion of Semantic Web has emerged as a prominent solution to the problem of organizing the immense information provided by World Wide Web, and its focus on supporting a better co-operation between humans and machines is noteworthy. Ontology forms the major component of Semantic Web in its realization. However, manual method of ontology construction is time-consuming, costly, error-prone and inflexible to change and in addition, it requires a complete participation of knowledge engineer or domain expert. To address this issue, researchers hoped that a semi-automatic or automatic process would result in faster and better ontology construction and enrichment. Ontology learning has become recently a major area of research, whose goal is to facilitate construction of ontologies, which reduces the effort in developing ontology for a new domain. However, there are few research studies that attempt to construct ontology from semi-structured Web pages. In this paper, we present a complete framework for ontology learning that facilitates the semi-automation of constructing and enriching web site ontology from semi structured Web pages. The proposed framework employs Web Content Mining and Web Usage mining in extracting conceptual relationship from Web. The main idea behind this concept was to incorporate the web author's ideas as well as web users’ intentions in the ontology development and its evolution.

  16. Exploring and linking biomedical resources through multidimensional semantic spaces

    National Research Council Canada - National Science Library

    Berlanga, Rafael; Jiménez-Ruiz, Ernesto; Nebot, Victoria

    .... The availability of comprehensive knowledge resources such as biomedical ontologies and integrated thesauri greatly facilitates this integration effort by means of semantic annotation, which allows...

  17. Semantic Web Technologies for Digital Libraries

    Directory of Open Access Journals (Sweden)

    Rajab Abd al-Hamed

    2007-09-01

    Full Text Available An article about the semantic web, it begins with defining the semantic web and its importance, then talks about the ontology relations, then the role of the semantic web in digital libraries, and its features which will serve digital libraries.

  18. The Ontology for Biomedical Investigations.

    Science.gov (United States)

    Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

    2016-01-01

    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

  19. The Ontology for Biomedical Investigations.

    Directory of Open Access Journals (Sweden)

    Anita Bandrowski

    Full Text Available The Ontology for Biomedical Investigations (OBI is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI and Phenotype Attribute and Trait Ontology (PATO without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT. The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org providing details on the people, policies, and issues being

  20. Ontology Evaluation:Consideration of Criteria, Approaches and Layers

    Directory of Open Access Journals (Sweden)

    Akram Fathian Dastgerdi

    2012-03-01

    Full Text Available Ontology is commonly used as a structure capturing knowledge about a certain area via providing relevant concepts and relations between them. Nowadays, because of the increase in designing ontologies in different domains, it is important to describe some criteria for selecting the most appropriate ontology. The purpose of this paper is to discuss the ontology evaluation criteria, approaches and layers. At first, different evaluation stages in ontology evaluation were explained. Then the most important approaches to ontology evaluation were described: included gold standard, task-based, data-driven and criteria based evaluation. Another part of this paper was about ontology evaluation criteria such as those mentioned by experts of ontology domain as well as the criteria that proposed by US National Center for ontological Research. Lastly, the levels of ontology evaluation, involved lexical, vocabulary, or data layer, hierarchy or taxonomy layer, other semantic relations layer, context or application level, syntactic level, structure, architecture and design layer were characterized.

  1. Semantic Web Technologies for the Adaptive Web

    DEFF Research Database (Denmark)

    Dolog, Peter

    2007-01-01

    Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web...... means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components...... are crucial to be formalized by the semantic web ontologies for adaptive web. We use examples from an eLearning domain to illustrate the principles which are broadly applicable to any information domain on the web....

  2. Fuzzy knowledge management for the semantic web

    CERN Document Server

    Ma, Zongmin; Yan, Li; Cheng, Jingwei

    2014-01-01

    This book goes to great depth concerning the fast growing topic of technologies and approaches of fuzzy logic in the Semantic Web. The topics of this book include fuzzy description logics and fuzzy ontologies, queries of fuzzy description logics and fuzzy ontology knowledge bases, extraction of fuzzy description logics and ontologies from fuzzy data models, storage of fuzzy ontology knowledge bases in fuzzy databases, fuzzy Semantic Web ontology mapping, and fuzzy rules and their interchange in the Semantic Web. The book aims to provide a single record of current research in the fuzzy knowledge representation and reasoning for the Semantic Web. The objective of the book is to provide the state of the art information to researchers, practitioners and graduate students of the Web intelligence and at the same time serve the knowledge and data engineering professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.

  3. Geo-Information (Lake Data Service Based on Ontology

    Directory of Open Access Journals (Sweden)

    Long-hua He

    2007-12-01

    Full Text Available Recently ontology research has received much attention in geo-information science and the concept of ontology is very important for spatial information concept modeling and data sharing, classification of geographical classes. More importantly, it enriches the semantic theory of spatial information. Geo-information services and geo-information interpretation and extraction are the two main applications of geo-ontology. Ontologies have great application potential for geo-information service.

  4. The effects of semantic radicals and phonetic radicals in Chinese phonogram recognition%形旁和声旁在形声字识别中的作用

    Institute of Scientific and Technical Information of China (English)

    王协顺; 吴岩; 赵思敏; 倪超; 张明

    2016-01-01

    形声字是由表示意义范畴的义符(形旁)和表示发音信息的声符(声旁)组合而成, 以往研究虽然肯定了声旁在形声字加工中的作用, 但对形旁的作用仍存在一定争议.结合行为和脑电技术, 采用汉字判断任务,以形旁和声旁均为独体字的形声字作为实验材料, 通过操纵形旁频率和声旁频率, 本研究进一步探讨了形旁和声旁在形声字识别中的作用.行为结果(实验 1)发现形旁频率并未引发反应时和错误率上的显著变化,而声旁频率在反应时和错误率上均产生了显著的效应, 相对于低频声旁, 高频声旁条件下的反应时更长、错误率更高.脑电结果(实验 2)发现, 相对于低频形旁, 高频形旁在前脑区引发了一个波幅更小的 N400; 而声旁频率不仅可以在全部脑区引发 N400 的变化, 同时在左脑的前、中脑区引发了 P200 的变化.相对于低频声旁,高频声旁所引发的P200波幅更小, N400波幅更大.两实验结果说明,在形声字识别中,形旁和声旁均可以产生作用, 但形旁的激活时间要晚于声旁, 且作用相对较弱.%The majority of Chinese characters are compound characters, and around 80% of the compound characters are phonograms which are comprised of a semantic radical and a phonetic radical. The semantic radical usually implies the meaning of the phonogram (e.g.,桐, tong2: tung, whose semantic radical is木, mu4: wood), and the phonetic radical offers a phonological clue for the pronunciation of its host phonogram (e.g.,桐, tong2: tung, whose phonetic radical is同, tong2: together/same). Since the semantic and phonetic radicals have different functional values, some researchers turned to investigate the issue whether their distinctive functions would generate different processing patterns during the phonogram recognition. However, regretfully, current results are confusing, with some studies reporting that the effect of the phonetic radicals

  5. Semantic Web Technologies for the Adaptive Web

    DEFF Research Database (Denmark)

    Dolog, Peter

    2007-01-01

    Ontologies and reasoning are the key terms brought into focus by the semantic web community. Formal representation of ontologies in a common data model on the web can be taken as a foundation for adaptive web technologies as well. This chapter describes how ontologies shared on the semantic web...... provide conceptualization for the links which are a main vehicle to access information on the web. The subject domain ontologies serve as constraints for generating only those links which are relevant for the domain a user is currently interested in. Furthermore, user model ontologies provide additional...... means for deciding which links to show, annotate, hide, generate, and reorder. The semantic web technologies provide means to formalize the domain ontologies and metadata created from them. The formalization enables reasoning for personalization decisions. This chapter describes which components...

  6. Agile development of ontologies through conversation

    Science.gov (United States)

    Braines, Dave; Bhattal, Amardeep; Preece, Alun D.; de Mel, Geeth

    2016-05-01

    Ontologies and semantic systems are necessarily complex but offer great potential in terms of their ability to fuse information from multiple sources in support of situation awareness. Current approaches do not place the ontologies directly into the hands of the end user in the field but instead hide them away behind traditional applications. We have been experimenting with human-friendly ontologies and conversational interactions to enable non-technical business users to interact with and extend these dynamically. In this paper we outline our approach via a worked example, covering: OWL ontologies, ITA Controlled English, Sensor/mission matching and conversational interactions between human and machine agents.

  7. Semantic Web Services with Web Ontology Language (OWL-S) - Specification of Agent-Services for DARPA Agent Markup Language (DAML)

    Science.gov (United States)

    2006-08-01

    needed. In addition, it will be important to conduct empirical evaluation of the applicability and benefits of OWL-S in developing and managing service...Sycara, and T. Nishimura, "Towards a Semantic Web Ecommerce ," in Proceedings of 6th Conference on Business Information Systems (BIS2003), Colorado...IEEE Computer Society . Also appears in IEEE Distributed Systems Online, Vol. 3(5), 2002. 24. Terry R. Payne, Rahul Singh, and Katia Sycara. "RCal

  8. Semantic web for integrated network analysis in biomedicine.

    Science.gov (United States)

    Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

    2009-03-01

    The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

  9. Engineering Ontologies

    OpenAIRE

    Borst, Pim; Akkermans, Hans; Top, Jan

    1997-01-01

    We analyse the construction as well as the role of ontologies in knowledge sharing and reuse for complex industrial applications. In this article, the practical use of ontologies in large-scale applications not restricted to knowledge-based systems is demonstrated, for the domain of engineering systems modelling, simulation and design. A general and formal ontology, called PHYSSYS, for dynamic physical systems is presented and its structuring principles are discussed. We show how the PHYSSYS ...

  10. Measuring Incoherence in Description Logic-Based Ontologies

    Science.gov (United States)

    Qi, Guilin; Hunter, Anthony

    Ontologies play a core role in the success of the Semantic Web as they provide a shared vocabulary for different resources and applications. Developing an error-free ontology is a difficult task. A common kind of error for an ontology is logical contradiction or incoherence. In this paper, we propose some approaches to measuring incoherence in DL-based ontologies. These measures give an ontology engineer important information for maintaining and evaluating ontologies. We implement the proposed approaches using the KAON2 reasoner and provide some preliminary but encouraging empirical results.

  11. Concept Approximation between Fuzzy Ontologies

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Fuzzy ontologies are efficient tools to handle fuzzy and uncertain knowledge on the semantic web; but there are heterogeneity problems when gaining interoperability among different fuzzy ontologies. This paper uses concept approximation between fuzzy ontologies based on instances to solve the heterogeneity problems. It firstly proposes an instance selection technology based on instance clustering and weighting to unify the fuzzy interpretation of different ontologies and reduce the number of instances to increase the efficiency. Then the paper resolves the problem of computing the approximations of concepts into the problem of computing the least upper approximations of atom concepts. It optimizes the search strategies by extending atom concept sets and defining the least upper bounds of concepts to reduce the searching space of the problem. An efficient algorithm for searching the least upper bounds of concept is given.

  12. Spatial information semantic query based on SPARQL

    Science.gov (United States)

    Xiao, Zhifeng; Huang, Lei; Zhai, Xiaofang

    2009-10-01

    How can the efficiency of spatial information inquiries be enhanced in today's fast-growing information age? We are rich in geospatial data but poor in up-to-date geospatial information and knowledge that are ready to be accessed by public users. This paper adopts an approach for querying spatial semantic by building an Web Ontology language(OWL) format ontology and introducing SPARQL Protocol and RDF Query Language(SPARQL) to search spatial semantic relations. It is important to establish spatial semantics that support for effective spatial reasoning for performing semantic query. Compared to earlier keyword-based and information retrieval techniques that rely on syntax, we use semantic approaches in our spatial queries system. Semantic approaches need to be developed by ontology, so we use OWL to describe spatial information extracted by the large-scale map of Wuhan. Spatial information expressed by ontology with formal semantics is available to machines for processing and to people for understanding. The approach is illustrated by introducing a case study for using SPARQL to query geo-spatial ontology instances of Wuhan. The paper shows that making use of SPARQL to search OWL ontology instances can ensure the result's accuracy and applicability. The result also indicates constructing a geo-spatial semantic query system has positive efforts on forming spatial query and retrieval.

  13. A Framework of Semantic Information Representation in Distributed Environments

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    An information representation framework is designed to overcome the problem of semantic heterogeneity in distributed environments in this paper. Emphasis is placed on establishing an XML-oriented semantic data model and the mapping between XML data based on a global ontology semantic view. The framework is implemented in Web Service, which enhances information process efficiency, accuracy and the semantic interoperability as well.

  14. Semantic understanding of Image content

    Directory of Open Access Journals (Sweden)

    D D Dhobale

    2011-05-01

    Full Text Available Large amounts of spatial data are becoming available today due to the rapid development of remote sensing techniques. Several retrieval systems are proposed to retrieve necessary, interested and effective information such as key- word based image retrieval and content based image retrieval. However, the results of these approaches are generally unsatisfactory, unpredictable and do not match human perception due to the well gap between visual features and semantic concepts. In this paper, we propose a new approach allowing semantic satellite image retrieval, describing the semantic image content and managing uncertain information. It is based on ontology model which represents spatial knowledge in order to provide semantic understanding of image content. Our retrieval system is based on two modules: ontological model merging and semantic strategic image retrieval. The first module allows developing ontological models which represent spatial knowledge of the satellite image, and managing uncertain information. The second module allows retrieving satellite images basing on their ontological model. In order to improve the quality of retrieval system and to facilitate the retrieval process, we propose two retrieval strategies which are the opportunist strategy and the hypothetic strategy. Our approach attempts to improve the quality of image retrieval, to reduce the semantic gap between visual features and semantic concepts and to provide an automatic solution for efficient satellite image retrieval.

  15. The ontology-based answers (OBA service: A connector for embedded usage of ontologies in applications

    Directory of Open Access Journals (Sweden)

    Jürgen eDönitz

    2012-10-01

    Full Text Available The semantic web depends on the use of ontologies to let electronic systems interpret contextualinformation. Optimally, the handling and access of ontologies should be completely transparent to theuser. As a means to this end, we have developed a service that attempts to bridge the gap betweenexperts in a certain knowledge domain, ontologists and application developers. The ontology-basedanswers (OBA service introduced here can be embedded into custom applications to grant access to theclasses of ontologies and their relations as most important structural features as well as to informationencoded in the relations between ontology classes. Thus computational biologists can benefit fromontologies without detailed knowledge about the respective ontology. The content of ontologies ismapped to a graph of connected objects which is compatible to the object-oriented programmingstyle in Java. Semantic functions implement knowledge about the complex semantics of anontology beyond the class hierarchy and partOf-relations. By using these OBA functions anapplication can, for example, provide a semantic search function, or (in the examples outlined mapan anatomical structure to the organs it belongs to. The semantic functions relieve the applicationdeveloper from the necessity of acquiring in-depth knowledge about the semantics and curationguidelines of the used ontologies by implementing the required knowledge. The architecture of theOBA service encapsulates the logic to process ontologies in order to achieve a separation from theapplication logic. A public server with the current plugins is available and can be used with theprovided connector in a custom application in scenarios analogous to the presented use cases. Theserver and the client are freely available if a project requires the use of custom plugins or nonpublicontologies.The OBA service and further documentation is available at: http://www.bioinf.med.unigoettingen.de/projects/oba

  16. Turning text into research networks: information retrieval and computational ontologies in the creation of scientific databases.

    Directory of Open Access Journals (Sweden)

    Flávio Ceci

    Full Text Available BACKGROUND: Web-based, free-text documents on science and technology have been increasing growing on the web. However, most of these documents are not immediately processable by computers slowing down the acquisition of useful information. Computational ontologies might represent a possible solution by enabling semantically machine readable data sets. But, the process of ontology creation, instantiation and maintenance is still based on manual methodologies and thus time and cost intensive. METHOD: We focused on a large corpus containing information on researchers, research fields, and institutions. We based our strategy on traditional entity recognition, social computing and correlation. We devised a semi automatic approach for the recognition, correlation and extraction of named entities and relations from textual documents which are then used to create, instantiate, and maintain an ontology. RESULTS: We present a prototype demonstrating the applicability of the proposed strategy, along with a case study describing how direct and indirect relations can be extracted from academic and professional activities registered in a database of curriculum vitae in free-text format. We present evidence that this system can identify entities to assist in the process of knowledge extraction and representation to support ontology maintenance. We also demonstrate the extraction of relationships among ontology classes and their instances. CONCLUSION: We have demonstrated that our system can be used for the conversion of research information in free text format into database with a semantic structure. Future studies should test this system using the growing number of free-text information available at the institutional and national levels.

  17. Semantic Observation Integration

    Directory of Open Access Journals (Sweden)

    Werner Kuhn

    2012-09-01

    Full Text Available Although the integration of sensor-based information into analysis and decision making has been a research topic for many years, semantic interoperability has not yet been reached. The advent of user-generated content for the geospatial domain, Volunteered Geographic Information (VGI, makes it even more difficult to establish semantic integration. This paper proposes a novel approach to integrating conventional sensor information and VGI, which is exploited in the context of detecting forest fires. In contrast to common logic-based semantic descriptions, we present a formal system using algebraic specifications to unambiguously describe the processing steps from natural phenomena to value-added information. A generic ontology of observations is extended and profiled for forest fire detection in order to illustrate how the sensing process, and transformations between heterogeneous sensing systems, can be represented as mathematical functions and grouped into abstract data types. We discuss the required ontological commitments and a possible generalization.

  18. Engineering Ontologies

    NARCIS (Netherlands)

    Borst, Pim; Akkermans, Hans; Top, Jan

    1997-01-01

    We analyse the construction as well as the role of ontologies in knowledge sharing and reuse for complex industrial applications. In this article, the practical use of ontologies in large-scale applications not restricted to knowledge-based systems is demonstrated, for the domain of engineering syst

  19. Microposts Ontology Construction Via Concept Extraction

    Directory of Open Access Journals (Sweden)

    Beenu Yadav

    2012-08-01

    Full Text Available The social networking website Facebook offers to its users a feature called “status updates” (or just “status”, which allows users to create Microposts directed to all their contacts, or a subset thereof. Readers can respond to Microposts, or in addition to that also click a “Like” button to show their appreciation for a certain Micropost. Adding semantic meaning in the sense of unambiguous intended ideas to such Microposts. We can make a start towards semantic web by adding semantic annotation to web resources. Ontology are used to specify meaning of annotations. Ontology provide a vocabulary for representing and communicating knowledge about some topic and a set of semantic relationships that hold among the terms in that vocabulary. For increasing the efficiency of ontology based application there is a need to develop a mechanism that reduces the manual work in developing ontology. In this paper, we proposed Microposts’ ontology construction. In this paper we present a method that extracts meaningfulknowledge from microposts shared in social platforms. This process involves different steps for the analysis of such microposts (extraction of keywords, named entities and their matching to ontological concepts.

  20. Ontology Based Feature Driven Development Life Cycle

    Directory of Open Access Journals (Sweden)

    Farheen Siddiqui

    2012-01-01

    Full Text Available The upcoming technology support for semantic web promises fresh directions for Software Engineering community. Also semantic web has its roots in knowledge engineering that provoke software engineers to look for application of ontology applications throughout the Software Engineering lifecycle. The internal components of a semantic web are "light weight", and may be of less quality standards than the externally visible modules. In fact the internal components are generated from external (ontological component. That's the reason agile development approaches such as feature driven development are suitable for applications internal component development. As yet there is no particular procedure that describes the role of ontology in FDD processes. Therefore we propose an ontology based feature driven development for semantic web application that can be used form application model development to feature design and implementation. Features are precisely defined in the OWL-based domain model. Transition from OWL based domain model to feature list is directly defined in transformation rules. On the other hand the ontology based overall model can be easily validated through automated tools. Advantages of ontology-based feature Driven development are also discussed.

  1. Semi-automated ontology generation and evolution

    Science.gov (United States)

    Stirtzinger, Anthony P.; Anken, Craig S.

    2009-05-01

    Extending the notion of data models or object models, ontology can provide rich semantic definition not only to the meta-data but also to the instance data of domain knowledge, making these semantic definitions available in machine readable form. However, the generation of an effective ontology is a difficult task involving considerable labor and skill. This paper discusses an Ontology Generation and Evolution Processor (OGEP) aimed at automating this process, only requesting user input when un-resolvable ambiguous situations occur. OGEP directly attacks the main barrier which prevents automated (or self learning) ontology generation: the ability to understand the meaning of artifacts and the relationships the artifacts have to the domain space. OGEP leverages existing lexical to ontological mappings in the form of WordNet, and Suggested Upper Merged Ontology (SUMO) integrated with a semantic pattern-based structure referred to as the Semantic Grounding Mechanism (SGM) and implemented as a Corpus Reasoner. The OGEP processing is initiated by a Corpus Parser performing a lexical analysis of the corpus, reading in a document (or corpus) and preparing it for processing by annotating words and phrases. After the Corpus Parser is done, the Corpus Reasoner uses the parts of speech output to determine the semantic meaning of a word or phrase. The Corpus Reasoner is the crux of the OGEP system, analyzing, extrapolating, and evolving data from free text into cohesive semantic relationships. The Semantic Grounding Mechanism provides a basis for identifying and mapping semantic relationships. By blending together the WordNet lexicon and SUMO ontological layout, the SGM is given breadth and depth in its ability to extrapolate semantic relationships between domain entities. The combination of all these components results in an innovative approach to user assisted semantic-based ontology generation. This paper will describe the OGEP technology in the context of the architectural

  2. The MMI Device Ontology: Enabling Sensor Integration

    Science.gov (United States)

    Rueda, C.; Galbraith, N.; Morris, R. A.; Bermudez, L. E.; Graybeal, J.; Arko, R. A.; Mmi Device Ontology Working Group

    2010-12-01

    The Marine Metadata Interoperability (MMI) project has developed an ontology for devices to describe sensors and sensor networks. This ontology is implemented in the W3C Web Ontology Language (OWL) and provides an extensible conceptual model and controlled vocabularies for describing heterogeneous instrument types, with different data characteristics, and their attributes. It can help users populate metadata records for sensors; associate devices with their platforms, deployments, measurement capabilities and restrictions; aid in discovery of sensor data, both historic and real-time; and improve the interoperability of observational oceanographic data sets. We developed the MMI Device Ontology following a community-based approach. By building on and integrating other models and ontologies from related disciplines, we sought to facilitate semantic interoperability while avoiding duplication. Key concepts and insights from various communities, including the Open Geospatial Consortium (eg., SensorML and Observations and Measurements specifications), Semantic Web for Earth and Environmental Terminology (SWEET), and W3C Semantic Sensor Network Incubator Group, have significantly enriched the development of the ontology. Individuals ranging from instrument designers, science data producers and consumers to ontology specialists and other technologists contributed to the work. Applications of the MMI Device Ontology are underway for several community use cases. These include vessel-mounted multibeam mapping sonars for the Rolling Deck to Repository (R2R) program and description of diverse instruments on deepwater Ocean Reference Stations for the OceanSITES program. These trials involve creation of records completely describing instruments, either by individual instances or by manufacturer and model. Individual terms in the MMI Device Ontology can be referenced with their corresponding Uniform Resource Identifiers (URIs) in sensor-related metadata specifications (e

  3. ImageSpace: An Environment for Image Ontology Management

    CERN Document Server

    Lu, Shiyong; Chebotko, Artem; Deng, Yu; Fotouhi, Farshad

    2009-01-01

    More and more researchers have realized that ontologies will play a critical role in the development of the Semantic Web, the next generation Web in which content is not only consumable by humans, but also by software agents. The development of tools to support ontology management including creation, visualization, annotation, database storage, and retrieval is thus extremely important. We have developed ImageSpace, an image ontology creation and annotation tool that features (1) full support for the standard web ontology language DAML+OIL; (2) image ontology creation, visualization, image annotation and display in one integrated framework; (3) ontology consistency assurance; and (4) storing ontologies and annotations in relational databases. It is expected that the availability of such a tool will greatly facilitate the creation of image repositories as islands of the Semantic Web.

  4. Anatomy Ontology Matching Using Markov Logic Networks

    Directory of Open Access Journals (Sweden)

    Chunhua Li

    2016-01-01

    Full Text Available The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

  5. 一种基于本体的知识库语义扩展搜索方法%Semantic Extended Search Approach Based on Ontology in Knowledge Base

    Institute of Scientific and Technical Information of China (English)

    万静; 王文聪; 易军凯

    2012-01-01

    To break through the limitations in traditional queries based on keyword search and improve search recall and precision, a semantic extended search approach, which is based on ontology in knowledge base, is proposed in this paper. This approach extends the user's search query, and sorts search results according to relevance analyses. Experimental results show that the approach in this paper can effectively improve the recall and precision.%为使知识库的信息搜索突破传统基于关键字查询的局限,提出一种基于本体的知识库语义扩展搜索方法.将本体和语义扩展引入知识库,对用户查询条件进行扩展搜索,通过相关度分析对搜索结果进行排序,使搜索效果得到优化.实验结果表明,该方法能提高搜索查全率和查准率.

  6. Evaluating the effect of annotation size on measures of semantic similarity

    KAUST Repository

    Kulmanov, Maxat

    2017-02-13

    Background: Ontologies are widely used as metadata in biological and biomedical datasets. Measures of semantic similarity utilize ontologies to determine how similar two entities annotated with classes from ontologies are, and semantic similarity is increasingly applied in applications ranging from diagnosis of disease to investigation in gene networks and functions of gene products.

  7. How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects.

    Science.gov (United States)

    Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A; Noy, Natalya F

    2013-05-01

    Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product. In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches.

  8. Where to Publish and Find Ontologies? A Survey of Ontology Libraries

    Science.gov (United States)

    d'Aquin, Mathieu; Noy, Natalya F.

    2011-01-01

    One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their domain and data, it will be much easier for them to “talk” to one another. Ontology libraries are the systems that collect ontologies from different sources and facilitate the tasks of finding, exploring, and using these ontologies. Thus ontology libraries can serve as a link in enabling diverse users and applications to discover, evaluate, use, and publish ontologies. In this paper, we provide a survey of the growing—and surprisingly diverse—landscape of ontology libraries. We highlight how the varying scope and intended use of the libraries a ects their features, content, and potential exploitation in applications. From reviewing eleven ontology libraries, we identify a core set of questions that ontology practitioners and users should consider in choosing an ontology library for finding ontologies or publishing their own. We also discuss the research challenges that emerge from this survey, for the developers of ontology libraries to address. PMID:22408576

  9. Where to Publish and Find Ontologies? A Survey of Ontology Libraries.

    Science.gov (United States)

    d'Aquin, Mathieu; Noy, Natalya F

    2012-03-01

    One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their domain and data, it will be much easier for them to "talk" to one another. Ontology libraries are the systems that collect ontologies from different sources and facilitate the tasks of finding, exploring, and using these ontologies. Thus ontology libraries can serve as a link in enabling diverse users and applications to discover, evaluate, use, and publish ontologies. In this paper, we provide a survey of the growing-and surprisingly diverse-landscape of ontology libraries. We highlight how the varying scope and intended use of the libraries a ects their features, content, and potential exploitation in applications. From reviewing eleven ontology libraries, we identify a core set of questions that ontology practitioners and users should consider in choosing an ontology library for finding ontologies or publishing their own. We also discuss the research challenges that emerge from this survey, for the developers of ontology libraries to address.

  10. The Role of Semantics in Translation Recognition: Effects of Number of Translations, Dominance of Translations and Semantic Relatedness of Multiple Translations

    Science.gov (United States)

    Laxen, Jannika; Lavaur, Jean-Marc

    2010-01-01

    This study aims to examine the influence of multiple translations of a word on bilingual processing in three translation recognition experiments during which French-English bilinguals had to decide whether two words were translations of each other or not. In the first experiment, words with only one translation were recognized as translations…

  11. Semantic Sensor Web

    Science.gov (United States)

    Sheth, A.; Henson, C.; Thirunarayan, K.

    2008-12-01

    Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the Semantic Sensor Web (SSW) [1] proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for situational knowledge. Kno.e.sis Center's approach to SSW is an evolutionary one. It adds semantic annotations to the existing standard sensor languages of the Sensor Web Enablement (SWE) defined by OGC. These annotations enhance primarily syntactic XML-based descriptions in OGC's SWE languages with microformats, and W3C's Semantic Web languages- RDF and OWL. In association with semantic annotation and semantic web capabilities including ontologies and rules, SSW supports interoperability, analysis and reasoning over heterogeneous multi-modal sensor data. In this presentation, we will also demonstrate a mashup with support for complex spatio-temporal-thematic queries [2] and semantic analysis that utilize semantic annotations, multiple ontologies and rules. It uses existing services (e.g., GoogleMap) and semantics enhanced SWE's Sensor Observation Service (SOS) over weather and road condition data from various sensors that are part of Ohio's transportation network. Our upcoming plans are to demonstrate end to end (heterogeneous sensor to application) semantics support and study scalability of SSW involving thousands of sensors to about a billion triples. Keywords: Semantic Sensor Web, Spatiotemporal thematic queries, Semantic Web Enablement, Sensor Observation Service [1] Amit Sheth, Cory Henson, Satya

  12. Understanding and using the meaning of statements in a bio-ontology: recasting the Gene Ontology in OWL

    Directory of Open Access Journals (Sweden)

    Aranguren Mikel

    2007-02-01

    Full Text Available Abstract The bio-ontology community falls into two camps: first we have biology domain experts, who actually hold the knowledge we wish to capture in ontologies; second, we have ontology specialists, who hold knowledge about techniques and best practice on ontology development. In the bio-ontology domain, these two camps have often come into conflict, especially where pragmatism comes into conflict with perceived best practice. One of these areas is the insistence of computer scientists on a well-defined semantic basis for the Knowledge Representation language being used. In this article, we will first describe why this community is so insistent. Second, we will illustrate this by examining the semantics of the Web Ontology Language and the semantics placed on the Directed Acyclic Graph as used by the Gene Ontology. Finally we will reconcile the two representations, including the broader Open Biomedical Ontologies format. The ability to exchange between the two representations means that we can capitalise on the features of both languages. Such utility can only arise by the understanding of the semantics of the languages being used. By this illustration of the usefulness of a clear, well-defined language semantics, we wish to promote a wider understanding of the computer science perspective amongst potential users within the biological community.

  13. Ontology-based multi-agent systems

    Energy Technology Data Exchange (ETDEWEB)

    Hadzic, Maja; Wongthongtham, Pornpit; Dillon, Tharam; Chang, Elizabeth [Digital Ecosystems and Business Intelligence Institute, Perth, WA (Australia)

    2009-07-01

    The Semantic web has given a great deal of impetus to the development of ontologies and multi-agent systems. Several books have appeared which discuss the development of ontologies or of multi-agent systems separately on their own. The growing interaction between agents and ontologies has highlighted the need for integrated development of these. This book is unique in being the first to provide an integrated treatment of the modeling, design and implementation of such combined ontology/multi-agent systems. It provides clear exposition of this integrated modeling and design methodology. It further illustrates this with two detailed case studies in (a) the biomedical area and (b) the software engineering area. The book is, therefore, of interest to researchers, graduate students and practitioners in the semantic web and web science area. (orig.)

  14. Ontology Supported Information Systems: A Review

    Directory of Open Access Journals (Sweden)

    Padmavathi, T.

    2014-12-01

    Full Text Available The exponential growth of information on the web far exceeds the capacity of present day information retrieval systems and search engines, making information integration on the web difficult. In order to overcome this, semantic web technologies were proposed by the World Wide Web Consortium (W3C to achieve a higher degree of automation and precision in information retrieval systems. Semantic web, with its promise to deliver machine understanding to the traditional web, has attracted a significant amount of research from academia as well as from industries. Semantic web is an extension of the current web in which data can be shared and reused across the internet. RDF and ontology are two essential components of the semantic web architecture which support a common framework for data storage and representation of data semantics, respectively. Ontologies being the backbone of semantic web applications, it is more relevant to study various approaches in their application, usage, and integration into web services. In this article, an effort has been made to review the research work being undertaken in the area of design and development of ontology supported information systems. This paper also briefly explains the emerging semantic web technologies and standards.

  15. The Orthology Ontology: development and applications.

    Science.gov (United States)

    Fernández-Breis, Jesualdo Tomás; Chiba, Hirokazu; Legaz-García, María Del Carmen; Uchiyama, Ikuo

    2016-06-04

    Computational comparative analysis of multiple genomes provides valuable opportunities to biomedical research. In particular, orthology analysis can play a central role in comparative genomics; it guides establishing evolutionary relations among genes of organisms and allows functional inference of gene products. However, the wide variations in current orthology databases necessitate the research toward the shareability of the content that is generated by different tools and stored in different structures. Exchanging the content with other research communities requires making the meaning of the content explicit. The need for a common ontology has led to the creation of the Orthology Ontology (ORTH) following the best practices in ontology construction. Here, we describe our model and major entities of the ontology that is implemented in the Web Ontology Language (OWL), followed by the assessment of the quality of the ontology and the application of the ORTH to existing orthology datasets. This shareable ontology enables the possibility to develop Linked Orthology Datasets and a meta-predictor of orthology through standardization for the representation of orthology databases. The ORTH is freely available in OWL format to all users at http://purl.org/net/orth . The Orthology Ontology can serve as a framework for the semantic standardization of orthology content and it will contribute to a better exploitation of orthology resources in biomedical research. The results demonstrate the feasibility of developing shareable datasets using this ontology. Further applications will maximize the usefulness of this ontology.

  16. Supporting Personal Semantic Annotations in P2P Semantic Wikis

    Science.gov (United States)

    Torres, Diego; Skaf-Molli, Hala; Díaz, Alicia; Molli, Pascal

    In this paper, we propose to extend Peer-to-Peer Semantic Wikis with personal semantic annotations. Semantic Wikis are one of the most successful Semantic Web applications. In semantic wikis, wikis pages are annotated with semantic data to facilitate the navigation, information retrieving and ontology emerging. Semantic data represents the shared knowledge base which describes the common understanding of the community. However, in a collaborative knowledge building process the knowledge is basically created by individuals who are involved in a social process. Therefore, it is fundamental to support personal knowledge building in a differentiated way. Currently there are no available semantic wikis that support both personal and shared understandings. In order to overcome this problem, we propose a P2P collaborative knowledge building process and extend semantic wikis with personal annotations facilities to express personal understanding. In this paper, we detail the personal semantic annotation model and show its implementation in P2P semantic wikis. We also detail an evaluation study which shows that personal annotations demand less cognitive efforts than semantic data and are very useful to enrich the shared knowledge base.

  17. Ontology Research

    OpenAIRE

    Welty, Christopher

    2003-01-01

    In this issue, I have collected a fairly broad, although by no means exhaustive, sampling of work in the field of ontology research. To define a field is often quite difficult; it is more a collection of people and ideas than it is a specific technology. To represent our field, I present six articles that cover several of the major thrusts of ontology research from the past decade.

  18. The Semantic SPASE

    Science.gov (United States)

    Hughes, S.; Crichton, D.; Thieman, J.; Ramirez, P.; King, T.; Weiss, M.

    2005-12-01

    The Semantic SPASE (Space Physics Archive Search and Extract) prototype demonstrates the use of semantic web technologies to capture, document, and manage the SPASE data model, support facet- and text-based search, and provide flexible and intuitive user interfaces. The SPASE data model, under development since late 2003 by a consortium of space physics domain experts, is intended to serve as the basis for interoperability between independent data systems. To develop the Semantic SPASE prototype, the data model was first analyzed to determine the inherit object classes and their attributes. These were entered into Stanford Medical Informatics' Protege ontology tool and annotated using definitions from the SPASE documentation. Further analysis of the data model resulted in the addition of class relationships. Finally attributes and relationships that support broad-scope interoperability were added from research associated with the Object-Oriented Data Technology task. To validate the ontology and produce a knowledge base, example data products were ingested. The capture of the data model as an ontology results in a more formal specification of the model. The Protege software is also a powerful management tool and supports plug-ins that produce several graphical notations as output. The stated purpose of the semantic web is to support machine understanding of web-based information. Protege provides an export capability to RDF/XML and RDFS/XML for this purpose. Several research efforts use RDF/XML knowledge bases to provide semantic search. MIT's Simile/Longwell project provides both facet- and text-based search using a suite of metadata browsers and the text-based search engine Lucene. Using the Protege generated RDF knowledge-base a semantic search application was easily built and deployed to run as a web application. Configuration files specify the object attributes and values to be designated as facets (i.e. search) constraints. Semantic web technologies provide

  19. Visual Ontology Construction for Digitized Art Image Retrieval

    Institute of Scientific and Technical Information of China (English)

    Shu-Qiang Jiang; Jun Du; Qing-Ming Huang; Tie-Jun Huang; Wen Gao

    2005-01-01

    Current investigations on visual information retrieval are generally content-based methods. The significant difference between similarity in Iow-level features and similarity in high-level semantic meanings is still a major challenge in the area of image retrieval. In this work, a scheme for constructing visual ontology to retrieve art images is proposed.The proposed ontology describes images in various aspects, including type & style, objects and global perceptual effects.Concepts in the ontology could be automatically derived. Various art image classification methods are employed based on low-level image features. Non-objective semantics are introduced, and how to express these semantics is given. The proposed ontology scheme could make users more naturally find visual information and thus narrows the "semantic gap".Experimental implementation demonstrates its good potential for retrieving art images in a human-centered manner.

  20. GOOSE: semantic search on internet connected sensors

    Science.gov (United States)

    Schutte, Klamer; Bomhof, Freek; Burghouts, Gertjan; van Diggelen, Jurriaan; Hiemstra, Peter; van't Hof, Jaap; Kraaij, Wessel; Pasman, Huib; Smith, Arthur; Versloot, Corne; de Wit, Joost

    2013-05-01

    More and more sensors are getting Internet connected. Examples are cameras on cell phones, CCTV cameras for traffic control as well as dedicated security and defense sensor systems. Due to the steadily increasing data volume, human exploitation of all this sensor data is impossible for effective mission execution. Smart access to all sensor data acts as enabler for questions such as "Is there a person behind this building" or "Alert me when a vehicle approaches". The GOOSE concept has the ambition to provide the capability to search semantically for any relevant information within "all" (including imaging) sensor streams in the entire Internet of sensors. This is similar to the capability provided by presently available Internet search engines which enable the retrieval of information on "all" web pages on the Internet. In line with current Internet search engines any indexing services shall be utilized cross-domain. The two main challenge for GOOSE is the Semantic Gap and Scalability. The GOOSE architecture consists of five elements: (1) an online extraction of primitives on each sensor stream; (2) an indexing and search mechanism for these primitives; (3) a ontology based semantic matching module; (4) a top-down hypothesis verification mechanism and (5) a controlling man-machine interface. This paper reports on the initial GOOSE demonstrator, which consists of the MES multimedia analysis platform and the CORTEX action recognition module. It also provides an outlook into future GOOSE development.

  1. ONSET: Automated foundational ontology selection and explanation

    CSIR Research Space (South Africa)

    Khan, Z

    2012-10-01

    Full Text Available ://www.meteck.org/files/onset/. Scenario 1: Semantic Management of Middleware. The tool was tested according to the requirements of [9] which is an application of the semantic web. Ontolog- ical choices of the test case include: descriptiveness, a multiplicative approach, possibilism... to use DOLCE only. Even when a domain ontology developer wants to consider using a FO, there is a prohibitive learning curve due to the considerable quantity of documentation and the new terminology it introduces. Seeing that FOs are bene cial...

  2. Constructing a Geology Ontology Using a Relational Database

    Science.gov (United States)

    Hou, W.; Yang, L.; Yin, S.; Ye, J.; Clarke, K.

    2013-12-01

    In geology community, the creation of a common geology ontology has become a useful means to solve problems of data integration, knowledge transformation and the interoperation of multi-source, heterogeneous and multiple scale geological data. Currently, human-computer interaction methods and relational database-based methods are the primary ontology construction methods. Some human-computer interaction methods such as the Geo-rule based method, the ontology life cycle method and the module design method have been proposed for applied geological ontologies. Essentially, the relational database-based method is a reverse engineering of abstracted semantic information from an existing database. The key is to construct rules for the transformation of database entities into the ontology. Relative to the human-computer interaction method, relational database-based methods can use existing resources and the stated semantic relationships among geological entities. However, two problems challenge the development and application. One is the transformation of multiple inheritances and nested relationships and their representation in an ontology. The other is that most of these methods do not measure the semantic retention of the transformation process. In this study, we focused on constructing a rule set to convert the semantics in a geological database into a geological ontology. According to the relational schema of a geological database, a conversion approach is presented to convert a geological spatial database to an OWL-based geological ontology, which is based on identifying semantics such as entities, relationships, inheritance relationships, nested relationships and cluster relationships. The semantic integrity of the transformation was verified using an inverse mapping process. In a geological ontology, an inheritance and union operations between superclass and subclass were used to present the nested relationship in a geochronology and the multiple inheritances

  3. A Semantic Approach to Describe Geospatial Resources

    Science.gov (United States)

    de Sousa, Sidney Roberto

    Geographic information systems (GIS) are increasingly using geospatial data from the Web to produce geographic information. One big challenge is to find the relevant data, which often is based on keywords or even file names. However, these approaches lack semantics. Thus, it is necessary to provide mechanisms to prepare data to help retrieval of semantically relevant data. This paper proposes an approach to attack this problem. This approach is based on semantic annotations that use geographic metadata and ontologies to describe heterogeneous geospatial data. Semantic annotations are RDF/XML files that rely on a FGDC metadata schema, filled with appropriate ontology terms, and stored in a XML database. The proposal is illustrated by a case study of semantic annotations of agricultural resources, using domain ontologies.

  4. A Simple Strategy to Start Domain Ontology from Scratch

    Directory of Open Access Journals (Sweden)

    Ivo Wolff Gersberg

    2014-01-01

    Full Text Available Aiming the usage of Domain Ontology as an educational tool for neophyte students and focusing in a fast and easy way to start Domain Ontology from scratch, the semantics are set aside to identify contexts of concepts (terms to build the ontology. Text Mining, Link Analysis and Graph Analysis create an abstract rough sketch of interactions between terms. This first rough sketch is presented to the expert providing insights into and inspires him to inform or communicate knowledge, through assertive sentences. Those assertive sentences subsidize the creation of the ontology. A web prototype tool to visualize the ontology and retrieve book contents is also presented.

  5. An Ontology-Based Service Matching Strategy in Grid Environments

    Institute of Scientific and Technical Information of China (English)

    YIN Nan; SHEN De-rong; YU Ge; KOU Yue; NIE Tie-zheng; CAO Yu

    2004-01-01

    An efficient ontology-based service searching scheme is put forward in this paper by introducing semantic information into grid systems.The ideas of ontology and OWL (Web ontology language) are applied to establish a uniform abstract concept model and standardization for grid services.We propose a general framework of ontology-based service discovery sub-system, which includes ontology storage module, context-based domain selection module and specific service matching module.Implementation policies are also presented in this paper.

  6. Complex Topographic Feature Ontology Patterns

    Science.gov (United States)

    Varanka, Dalia E.; Jerris, Thomas J.

    2015-01-01

    Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

  7. 基于本体的信息系统引论%On Ontology-based Information Systems

    Institute of Scientific and Technical Information of China (English)

    刘柏嵩

    2003-01-01

    Since Tim Bemers-Lee, current W3C chairman, first proposed the concept of Semantic Web, it is be-coming a hot topic in computer information processing area. Ontologies are playing a key role in the Semantic Web, ex-tending syntactic interoperability to semantic intemperability by providing a source of shared and precisely defined terms.The paper analyzes the requirement of information systems for ontology languages. The current popular ontology languages are also discussed.

  8. A Posteriori Ontology Engineering for Data-Driven Science

    Energy Technology Data Exchange (ETDEWEB)

    Gessler, Damian Dg; Joslyn, Cliff A.; Verspoor, Karin M.

    2013-05-28

    Science—and biology in particular—has a rich tradition in categorical knowledge management. This continues today in the generation and use of formal ontologies. Unfortunately, the link between hard data and ontological content is predominately qualitative, not quantitative. The usual approach is to construct ontologies of qualitative concepts, and then annotate the data to the ontologies. This process has seen great value, yet it is laborious, and the success to which ontologies are managing and organizing the full information content of the data is uncertain. An alternative approach is the converse: use the data itself to quantitatively drive ontology creation. Under this model, one generates ontologies at the time they are needed, allowing them to change as more data influences both their topology and their concept space. We outline a combined approach to achieve this, taking advantage of two technologies, the mathematical approach of Formal Concept Analysis (FCA) and the semantic web technologies of the Web Ontology Language (OWL).

  9. Towards a core ontology for integrating ecological and environmental ontologies to enable improved data interoperability

    Science.gov (United States)

    Bowers, S.; Madin, J.; Jones, M.; Schildhauer, M.; Ludaescher, B.

    2007-12-01

    Research in the ecological and environmental sciences increasingly relies on the integration of traditionally small, focused studies to form larger datasets for synthetic analyses. However, a broad range of data types, structures, and semantic subtleties occur in ecological data, making data discovery and integration a difficult and time-consuming task. Our work focuses on capturing the subtleties of scientific data through semantic annotations, which involve linking ecological data to concepts and relationships in domain-specific ontologies, thereby enabling more advanced forms of data discovery and integration. A variety of ontologies related to ecological data are actively being developed, ranging from low-level and highly focused vocabularies to high-level models and classifications. However, as the number of ontologies and their included terms increase, organizing these into a coherent framework useful for data annotation becomes increasingly complex (we note that similar issues have been recognized within the molecular biology and bioinformatics communities). We describe a core ontology model for semantic annotation that provides a structured approach for integrating the growing number of ecology-relevant ontologies. The ontology defines the notion of "scientific observation" as a unifying concept for capturing the basic semantics of ecological data. Observations are distinguished at the level of the entity (e.g., location, time, thing, concept), and characteristics of an entity (e.g., height, name, color) are measured (named or classified) as data. The ontology permits observations to be related via context (such as spatial or temporal containment), further supporting the discovery and automated comparison and alignment (e.g., merging) of heterogeneous data. The core ontology also defines a set of extension points that can be used to either directly build new domain ontologies (as extension ontologies), or to provide a common basis to which existing

  10. Oceanographic ontology-based spatial knowledge query

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The construction of oceanographic ontologies is fundamental to the "digital ocean". Therefore, on the basis of introduction of new concept of oceanographic ontology, an oceanographic ontology-based spatial knowledge query (OOBSKQ) method was proposed and developed. Because the method uses a natural language to describe query conditions and the query result is highly integrated knowledge,it can provide users with direct answers while hiding the complicated computation and reasoning processes, and achieves intelligent,automatic oceanographic spatial information query on the level of knowledge and semantics. A case study of resource and environmental application in bay has shown the implementation process of the method and its feasibility and usefulness.

  11. Multiple ontologies in action: composite annotations for biosimulation models.

    Science.gov (United States)

    Gennari, John H; Neal, Maxwell L; Galdzicki, Michal; Cook, Daniel L

    2011-02-01

    There now exists a rich set of ontologies that provide detailed semantics for biological entities of interest. However, there is not (nor should there be) a single source ontology that provides all the necessary semantics for describing biological phenomena. In the domain of physiological biosimulation models, researchers use annotations to convey semantics, and many of these annotations require the use of multiple reference ontologies. Therefore, we have developed the idea of composite annotations that access multiple ontologies to capture the physics-based meaning of model variables. These composite annotations provide the semantic expressivity needed to disambiguate the often-complex features of biosimulation models, and can be used to assist with model merging and interoperability. In this paper, we demonstrate the utility of composite annotations for model merging by describing their use within SemGen, our semantics-based model composition software. More broadly, if orthogonal reference ontologies are to meet their full potential, users need tools and methods to connect and link these ontologies. Our composite annotations and the SemGen tool provide one mechanism for leveraging multiple reference ontologies.

  12. Web Service Description and Discovery Based on Semantic Model

    Institute of Scientific and Technical Information of China (English)

    YANG Xuemei; XU Lizhen; DONG Yisheng; WANG Yongli

    2006-01-01

    A novel semantic model of Web service description and discovery was proposed through an extension for profile model of Web ontology language for services (OWL-S) in this paper.Similarity matching of Web services was implemented through computing weighted summation of semantic similarity value based on specific domain ontology and dynamical satisfy extent evaluation for quality of service (QoS).Experiments show that the provided semantic matching model is efficient.

  13. Semantic Web status model

    CSIR Research Space (South Africa)

    Gerber, AJ

    2006-06-01

    Full Text Available for reasoning systems [Bech- hofer et al., 2004; McGuinness and van Harmelen, 2004; Smith et al., 2004]. DL is a set of knowledge representation formalisms with semantic characterisation based on stan- dard first-order logics. DL offers a formal foundation... is a knowledge representation language capturing the syntax (ontology) as well as the semantics (rules) of a specific domain [McGuin- ness et al., 2002; McGuinness and van Harmelen, 2004]. Currently, OWL is the W3C technology representing...

  14. Semantator: semantic annotator for converting biomedical text to linked data.

    Science.gov (United States)

    Tao, Cui; Song, Dezhao; Sharma, Deepak; Chute, Christopher G

    2013-10-01

    More than 80% of biomedical data is embedded in plain text. The unstructured nature of these text-based documents makes it challenging to easily browse and query the data of interest in them. One approach to facilitate browsing and querying biomedical text is to convert the plain text to a linked web of data, i.e., converting data originally in free text to structured formats with defined meta-level semantics. In this paper, we introduce Semantator (Semantic Annotator), a semantic-web-based environment for annotating data of interest in biomedical documents, browsing and querying the annotated data, and interactively refining annotation results if needed. Through Semantator, information of interest can be either annotated manually or semi-automatically using plug-in information extraction tools. The annotated results will be stored in RDF and can be queried using the SPARQL query language. In addition, semantic reasoners can be directly applied to the annotated data for consistency checking and knowledge inference. Semantator has been released online and was used by the biomedical ontology community who provided positive feedbacks. Our evaluation results indicated that (1) Semantator can perform the annotation functionalities as designed; (2) Semantator can be adopted in real applications in clinical and transactional research; and (3) the annotated results using Semantator can be easily used in Semantic-web-based reasoning tools for further inference.

  15. SUGOI: automated ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2015-04-01

    Full Text Available A foundational ontology can solve interoperability issues among the domain ontologies aligned to it. However, several foundational ontologies have been developed, hence such interoperability issues exist among domain ontologies. The novel SUGOI tool...

  16. Ontology modeling in physical asset integrity management

    CERN Document Server

    Yacout, Soumaya

    2015-01-01

    This book presents cutting-edge applications of, and up-to-date research on, ontology engineering techniques in the physical asset integrity domain. Though a survey of state-of-the-art theory and methods on ontology engineering, the authors emphasize essential topics including data integration modeling, knowledge representation, and semantic interpretation. The book also reflects novel topics dealing with the advanced problems of physical asset integrity applications such as heterogeneity, data inconsistency, and interoperability existing in design and utilization. With a distinctive focus on applications relevant in heavy industry, Ontology Modeling in Physical Asset Integrity Management is ideal for practicing industrial and mechanical engineers working in the field, as well as researchers and graduate concerned with ontology engineering in physical systems life cycles. This book also: Introduces practicing engineers, research scientists, and graduate students to ontology engineering as a modeling techniqu...

  17. An ontology design pattern for surface water features

    Science.gov (United States)

    Sinha, Gaurav; Mark, David; Kolas, Dave; Varanka, Dalia; Romero, Boleslo E.; Feng, Chen-Chieh; Usery, E. Lynn; Liebermann, Joshua; Sorokine, Alexandre

    2014-01-01

    Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities exist due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology for other more context-dependent ontologies. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex or specialized surface water ontologies. A fundamental distinction is made in this ontology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is implemented in OWL, but Description Logic axioms and a detailed explanation is provided in this paper. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. Also provided is a discussion of why there is a need to complement the pattern with other ontologies, especially the previously developed Surface Network pattern. Finally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through an annotated geospatial dataset and sample queries using the classes of the Surface Water pattern.

  18. A Framework for Business Intelligence Application using Ontological Classification

    CERN Document Server

    Martin, A; Venkatesan, V Prasanna

    2011-01-01

    Every business needs knowledge about their competitors to survive better. One of the information repositories is web. Retrieving Specific information from the web is challenging. An Ontological model is developed to capture specific information by using web semantics. From the Ontology model, the relations between the data are mined using decision tree. From all these a new framework is developed for Business Intelligence.

  19. Ontology Extraction Tools: An Empirical Study with Educators

    Science.gov (United States)

    Hatala, M.; Gasevic, D.; Siadaty, M.; Jovanovic, J.; Torniai, C.

    2012-01-01

    Recent research in Technology-Enhanced Learning (TEL) demonstrated several important benefits that semantic technologies can bring to the TEL domain. An underlying assumption for most of these research efforts is the existence of a domain ontology. The second unspoken assumption follows that educators will build domain ontologies for their…

  20. Ontology Extraction Tools: An Empirical Study with Educators

    Science.gov (United States)

    Hatala, M.; Gasevic, D.; Siadaty, M.; Jovanovic, J.; Torniai, C.

    2012-01-01

    Recent research in Technology-Enhanced Learning (TEL) demonstrated several important benefits that semantic technologies can bring to the TEL domain. An underlying assumption for most of these research efforts is the existence of a domain ontology. The second unspoken assumption follows that educators will build domain ontologies for their…

  1. Uncertainty modeling process for semantic technology

    Directory of Open Access Journals (Sweden)

    Rommel N. Carvalho

    2016-08-01

    Full Text Available The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST, a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

  2. Ontology Localization

    OpenAIRE

    2009-01-01

    Nuestra meta principal en esta tesis es proponer una solución para construir una ontología multilingüe, a través de la localización automática de una ontología. La noción de localización viene del área de Desarrollo de Software que hace referencia a la adaptación de un producto de software a un ambiente no nativo. En la Ingeniería Ontológica, la localización de ontologías podría ser considerada como un subtipo de la localización de software en el cual el producto es un modelo compartido de un...

  3. Logical Gene Ontology Annotations (GOAL): exploring gene ontology annotations with OWL.

    Science.gov (United States)

    Jupp, Simon; Stevens, Robert; Hoehndorf, Robert

    2012-04-24

    Ontologies such as the Gene Ontology (GO) and their use in annotations make cross species comparisons of genes possible, along with a wide range of other analytical activities. The bio-ontologies community, in particular the Open Biomedical Ontologies (OBO) community, have provided many other ontologies and an increasingly large volume of annotations of gene products that can be exploited in query and analysis. As many annotations with different ontologies centre upon gene products, there is a possibility to explore gene products through multiple ontological perspectives at the same time. Questions could be asked that link a gene product's function, process, cellular location, phenotype and disease. Current tools, such as AmiGO, allow exploration of genes based on their GO annotations, but not through multiple ontological perspectives. In addition, the semantics of these ontology's representations should be able to, through automated reasoning, afford richer query opportunities of the gene product annotations than is currently possible. To do this multi-perspective, richer querying of gene product annotations, we have created the Logical Gene Ontology, or GOAL ontology, in OWL that combines the Gene Ontology, Human Disease Ontology and the Mammalian Phenotype Ontology, together with classes that represent the annotations with these ontologies for mouse gene products. Each mouse gene product is represented as a class, with the appropriate relationships to the GO aspects, phenotype and disease with which it has been annotated. We then use defined classes to query these protein classes through automated reasoning, and to build a complex hierarchy of gene products. We have presented this through a Web interface that allows arbitrary queries to be constructed and the results displayed. This standard use of OWL affords a rich interaction with Gene Ontology, Human Disease Ontology and Mammalian Phenotype Ontology annotations for the mouse, to give a fine partitioning of

  4. Aber-OWL: a framework for ontology-based data access in biology

    KAUST Repository

    Hoehndorf, Robert

    2015-01-28

    Background: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning. Results: We have developed the Aber-OWL infrastructure that provides reasoning services for bio-ontologies. Aber-OWL consists of an ontology repository, a set of web services and web interfaces that enable ontology-based semantic access to biological data and literature. Aber-OWL is freely available at http://aber-owl.net. Conclusions: Aber-OWL provides a framework for automatically accessing information that is annotated with ontologies or contains terms used to label classes in ontologies. When using Aber-OWL, access to ontologies and data annotated with them is not merely based on class names or identifiers but rather on the knowledge the ontologies contain and the inferences that can be drawn from it.

  5. Application of Ontologies for Big Earth Data

    Science.gov (United States)

    Huang, T.; Chang, G.; Armstrong, E. M.; Boening, C.

    2014-12-01

    Connected data is smarter data! Earth Science research infrastructure must do more than just being able to support temporal, geospatial discovery of satellite data. As the Earth Science data archives continue to expand across NASA data centers, the research communities are demanding smarter data services. A successful research infrastructure must be able to present researchers the complete picture, that is, datasets with linked citations, related interdisciplinary data, imageries, current events, social media discussions, and scientific data tools that are relevant to the particular dataset. The popular Semantic Web for Earth and Environmental Terminology (SWEET) ontologies is a collection of ontologies and concepts designed to improve discovery and application of Earth Science data. The SWEET ontologies collection was initially developed to capture the relationships between keywords in the NASA Global Change Master Directory (GCMD). Over the years this popular ontologies collection has expanded to cover over 200 ontologies and 6000 concepts to enable scalable classification of Earth system science concepts and Space science. This presentation discusses the semantic web technologies as the enabling technology for data-intensive science. We will discuss the application of the SWEET ontologies as a critical component in knowledge-driven research infrastructure for some of the recent projects, which include the DARPA Ontological System for Context Artifact and Resources (OSCAR), 2013 NASA ACCESS Virtual Quality Screening Service (VQSS), and the 2013 NASA Sea Level Change Portal (SLCP) projects. The presentation will also discuss the benefits in using semantic web technologies in developing research infrastructure for Big Earth Science Data in an attempt to "accommodate all domains and provide the necessary glue for information to be cross-linked, correlated, and discovered in a semantically rich manner." [1] [1] Savas Parastatidis: A platform for all that we know

  6. Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning.

    Directory of Open Access Journals (Sweden)

    Robert Hoehndorf

    Full Text Available Researchers design ontologies as a means to accurately annotate and integrate experimental data across heterogeneous and disparate data- and knowledge bases. Formal ontologies make the semantics of terms and relations explicit such that automated reasoning can be used to verify the consistency of knowledge. However, many biomedical ontologies do not sufficiently formalize the semantics of their relations and are therefore limited with respect to automated reasoning for large scale data integration and knowledge discovery. We describe a method to improve automated reasoning over biomedical ontologies and identify several thousand contradictory class definitions. Our approach aligns terms in biomedical ontologies with foundational classes in a top-level ontology and formalizes composite relations as class expressions. We describe the semi-automated repair of contradictions and demonstrate expressive queries over interoperable ontologies. Our work forms an important cornerstone for data integration, automatic inference and knowledge discovery based on formal representations of knowledge. Our results and analysis software are available at http://bioonto.de/pmwiki.php/Main/ReasonableOntologies.

  7. Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Oellrich, Anika; Rebholz-Schuhmann, Dietrich; Schofield, Paul N; Gkoutos, Georgios V

    2011-01-01

    Researchers design ontologies as a means to accurately annotate and integrate experimental data across heterogeneous and disparate data- and knowledge bases. Formal ontologies make the semantics of terms and relations explicit such that automated reasoning can be used to verify the consistency of knowledge. However, many biomedical ontologies do not sufficiently formalize the semantics of their relations and are therefore limited with respect to automated reasoning for large scale data integration and knowledge discovery. We describe a method to improve automated reasoning over biomedical ontologies and identify several thousand contradictory class definitions. Our approach aligns terms in biomedical ontologies with foundational classes in a top-level ontology and formalizes composite relations as class expressions. We describe the semi-automated repair of contradictions and demonstrate expressive queries over interoperable ontologies. Our work forms an important cornerstone for data integration, automatic inference and knowledge discovery based on formal representations of knowledge. Our results and analysis software are available at http://bioonto.de/pmwiki.php/Main/ReasonableOntologies.

  8. Pedagogically-Driven Ontology Network for Conceptualizing the e-Learning Assessment Domain

    Science.gov (United States)

    Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura

    2015-01-01

    The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…

  9. An Approach to Folksonomy-Based Ontology Maintenance for Learning Environments

    Science.gov (United States)

    Gasevic, D.; Zouaq, Amal; Torniai, Carlo; Jovanovic, J.; Hatala, Marek

    2011-01-01

    Recent research in learning technologies has demonstrated many promising contributions from the use of ontologies and semantic web technologies for the development of advanced learning environments. In spite of those benefits, ontology development and maintenance remain the key research challenges to be solved before ontology-enhanced learning…

  10. Pedagogically-Driven Ontology Network for Conceptualizing the e-Learning Assessment Domain

    Science.gov (United States)

    Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura

    2015-01-01

    The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…

  11. Ontology Merging as Social Choice: Judgment Aggregation under the Open World Assumption

    NARCIS (Netherlands)

    Porello, D.; Endriss, U.

    2014-01-01

    The problem of merging several ontologies has important applications in the Semantic Web, medical ontology engineering and other domains where information from several distinct sources needs to be integrated in a coherent manner. We propose to view ontology merging as a problem of social choice,

  12. Using MathML to Represent Units of Measurement for Improved Ontology Alignment

    NARCIS (Netherlands)

    Do, C.; Pauwels, E.J.

    2013-01-01

    Ontologies provide a formal description of concepts and their relationships in a knowledge domain. The goal of ontology alignment is to identify semantically matching concepts and relationships across independently developed ontologies that purport to describe the same knowledge. In order to handle

  13. Ontology-Based Retrieval of Spatially Related Objects for Location Based Services

    Science.gov (United States)

    Haav, Hele-Mai; Kaljuvee, Aivi; Luts, Martin; Vajakas, Toivo

    Advanced Location Based Service (LBS) applications have to integrate information stored in GIS, information about users' preferences (profile) as well as contextual information and information about application itself. Ontology engineering provides methods to semantically integrate several data sources. We propose an ontology-driven LBS development framework: the paper describes the architecture of ontologies and their usage for retrieval of spatially related objects relevant to the user. Our main contribution is to enable personalised ontology driven LBS by providing a novel approach for defining personalised semantic spatial relationships by means of ontologies. The approach is illustrated by an industrial case study.

  14. Constructing Virtual Documents for Keyword Based Concept Search in Web Ontology

    Directory of Open Access Journals (Sweden)

    Sapna Paliwal

    2013-04-01

    Full Text Available Web ontologies are structural frameworks for organizing information in semantics web and provide shared concepts. Ontology formally represents knowledge or information about particular entity as a set of concepts within a particular domain on semantic web. Web ontology helps to describe concepts within domain and also help us to enables semantic interoperability between two different applications byusing Falcons concept search. We can facilitate concept searching and ontologies reusing. Constructing virtual documents is a keyword based search in ontology. The proposed method helps us to find how search engine help user to find out ontologies in less time so we can satisfy their needs. It include some supportive technologies with new technique is to constructing virtual documents of concepts for keywordbased search and based on population scheme we rank the concept and ontologies, a way to generate structured snippets according to query. In this concept we can report the user feedback and usabilityevolution.

  15. An ontology for sensor networks

    Science.gov (United States)

    Compton, Michael; Neuhaus, Holger; Bermudez, Luis; Cox, Simon

    2010-05-01

    Sensors and networks of sensors are important ways of monitoring and digitizing reality. As the number and size of sensor networks grows, so too does the amount of data collected. Users of such networks typically need to discover the sensors and data that fit their needs without necessarily understanding the complexities of the network itself. The burden on users is eased if the network and its data are expressed in terms of concepts familiar to the users and their job functions, rather than in terms of the network or how it was designed. Furthermore, the task of collecting and combining data from multiple sensor networks is made easier if metadata about the data and the networks is stored in a format and conceptual models that is amenable to machine reasoning and inference. While the OGC's (Open Geospatial Consortium) SWE (Sensor Web Enablement) standards provide for the description and access to data and metadata for sensors, they do not provide facilities for abstraction, categorization, and reasoning consistent with standard technologies. Once sensors and networks are described using rich semantics (that is, by using logic to describe the sensors, the domain of interest, and the measurements) then reasoning and classification can be used to analyse and categorise data, relate measurements with similar information content, and manage, query and task sensors. This will enable types of automated processing and logical assurance built on OGC standards. The W3C SSN-XG (Semantic Sensor Networks Incubator Group) is producing a generic ontology to describe sensors, their environment and the measurements they make. The ontology provides definitions for the structure of sensors and observations, leaving the details of the observed domain unspecified. This allows abstract representations of real world entities, which are not observed directly but through their observable qualities. Domain semantics, units of measurement, time and time series, and location and mobility

  16. Discovery and Selection of Semantic Web Services

    CERN Document Server

    Wang, Xia

    2013-01-01

    For advanced web search engines to be able not only to search for semantically related information dispersed over different web pages, but also for semantic services providing certain functionalities, discovering semantic services is the key issue. Addressing four problems of current solution, this book presents the following contributions. A novel service model independent of semantic service description models is proposed, which clearly defines all elements necessary for service discovery and selection. It takes service selection as its gist and improves efficiency. Corresponding selection algorithms and their implementation as components of the extended Semantically Enabled Service-oriented Architecture in the Web Service Modeling Environment are detailed. Many applications of semantic web services, e.g. discovery, composition and mediation, can benefit from a general approach for building application ontologies. With application ontologies thus built, services are discovered in the same way as with single...

  17. Tutorial on Protein Ontology Resources.

    Science.gov (United States)

    Arighi, Cecilia N; Drabkin, Harold; Christie, Karen R; Ross, Karen E; Natale, Darren A

    2017-01-01

    The Protein Ontology (PRO) is the reference ontology for proteins in the Open Biomedical Ontologies (OBO) foundry and consists of three sub-ontologies representing protein classes of homologous genes, proteoforms (e.g., splice isoforms, sequence variants, and post-translationally modified forms), and protein complexes. PRO defines classes of proteins and protein complexes, both species-specific and species nonspecific, and indicates their relationships in a hierarchical framework, supporting accurate protein annotation at the appropriate level of granularity, analyses of protein conservation across species, and semantic reasoning. In the first section of this chapter, we describe the PRO framework including categories of PRO terms and the relationship of PRO to other ontologies and protein resources. Next, we provide a tutorial about the PRO website ( proconsortium.org ) where users can browse and search the PRO hierarchy, view reports on individual PRO terms, and visualize relationships among PRO terms in a hierarchical table view, a multiple sequence alignment view, and a Cytoscape network view. Finally, we describe several examples illustrating the unique and rich information available in PRO.

  18. Knowledge Organization Systems for Semantic Digital Libraries

    OpenAIRE

    Babu, Preedip Balaji; Sarangi, Amit K; Madalli, Devika P.

    2012-01-01

    As the traditional knowledge organization systems (KOS) like classification, thesauri are paving way for ontologies, transtechnological data models and semantic networks of data exchange provide impetus for developing semantic digital libraries. This paper attempts to find the KOS in the early digital libraries, and how they can be integrated with the digital library architectures using emergent semantic technologies and data. Metadata remains as a core area at the heart o...

  19. A Semantics-Based Approach to Retrieving Biomedical Information

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik; Zambach, Sine

    2011-01-01

    ontologies’, i.e., ontologies providing increasingly specialised concepts reflecting the phrase structure of natural language. Furthermore, we propose a novel so called ontological semantics which maps noun phrases from texts and queries into nodes in the generative ontology. This enables an advanced form......This paper describes an approach to representing, organising, and accessing conceptual content of biomedical texts using a formal ontology. The ontology is based on UMLS resources supplemented with domain ontologies developed in the project. The approach introduces the notion of ‘generative...

  20. Contributions to a Conceptual Ontology for Wittgenstein

    DEFF Research Database (Denmark)

    Addis, Mark; Brock, Steen; Pichler, Alois

    2015-01-01

    A conceptual ontology was used to semantically enrich the Wittgenstein Archives at the University of Bergen’s taxonomy for Wittgenstein Source to facilitate improved searching in the areas of the philosophies of mathematics and psychology. The classes and sub-classes of the multilingual taxonomy...

  1. Contributions to a Conceptual Ontology for Wittgenstein

    DEFF Research Database (Denmark)

    Addis, Mark; Brock, Steen; Pichler, Alois

    2015-01-01

    A conceptual ontology was used to semantically enrich the Wittgenstein Archives at the University of Bergen’s taxonomy for Wittgenstein Source to facilitate improved searching in the areas of the philosophies of mathematics and psychology. The classes and sub-classes of the multilingual taxonomy...

  2. NCBO Technology: Powering semantically aware applications.

    Science.gov (United States)

    Whetzel, Patricia L

    2013-04-15

    As new biomedical technologies are developed, the amount of publically available biomedical data continues to increase. To help manage these vast and disparate data sources, researchers have turned to the Semantic Web. Specifically, ontologies are used in data annotation, natural language processing, information retrieval, clinical decision support, and data integration tasks. The development of software applications to perform these tasks requires the integration of Web services to incorporate the wide variety of ontologies used in the health care and life sciences. The National Center for Biomedical Ontology, a National Center for Biomedical Computing created under the NIH Roadmap, developed BioPortal, which provides access to one of the largest repositories of biomedical ontologies. The NCBO Web services provide programmtic access to these ontologies and can be grouped into four categories; Ontology, Mapping, Annotation, and Data Access. The Ontology Web services provide access to ontologies, their metadata, ontology versions, downloads, navigation of the class hierarchy (parents, children, siblings) and details of each term. The Mapping Web services provide access to the millions of ontology mappings published in BioPortal. The NCBO Annotator Web service "tags" text automatically with terms from ontologies in BioPortal, and the NCBO Resource Index Web services provides access to an ontology-based index of public, online data resources. The NCBO Widgets package the Ontology Web services for use directly in Web sites. The functionality of the NCBO Web services and widgets are incorporated into semantically aware applications for ontology development and visualization, data annotation, and data integration. This overview will describe these classes of applications, discuss a few examples of each type, and which NCBO Web services are used by these applications.

  3. Evaluating the Semantic Web: A Task-Based Approach

    Science.gov (United States)

    Sabou, Marta; Gracia, Jorge; Angeletou, Sofia; D'Aquin, Mathieu; Motta, Enrico

    The increased availability of online knowledge has led to the design of several algorithms that solve a variety of tasks by harvesting the Semantic Web, i.e., by dynamically selecting and exploring a multitude of online ontologies. Our hypothesis is that the performance of such novel algorithms implicitly provides an insight into the quality of the used ontologies and thus opens the way to a task-based evaluation of the Semantic Web. We have investigated this hypothesis by studying the lessons learnt about online ontologies when used to solve three tasks: ontology matching, folksonomy enrichment, and word sense disambiguation. Our analysis leads to a suit of conclusions about the status of the Semantic Web, which highlight a number of strengths and weaknesses of the semantic information available online and complement the findings of other analysis of the Semantic Web landscape.

  4. Ontology Requirements Specification

    OpenAIRE

    Suárez-Figueroa, Mari Carmen; Gómez-Pérez, A.

    2012-01-01

    The goal of the ontology requirements specification activity is to state why the ontology is being built, what its intended uses are, who the end users are, and which requirements the ontology should fulfill. This chapter presents detailed methodological guidelines for specifying ontology requirements efficiently. These guidelines will help ontology engineers to capture ontology requirements and produce the ontology requirements specification document (ORSD). The ORSD will play a key role dur...

  5. Knowledge Discovery from Biomedical Ontologies in Cross Domains.

    Science.gov (United States)

    Shen, Feichen; Lee, Yugyung

    2016-01-01

    In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies.

  6. Knowledge Discovery from Biomedical Ontologies in Cross Domains

    Science.gov (United States)

    Shen, Feichen; Lee, Yugyung

    2016-01-01

    In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies. PMID:27548262

  7. Nuclear Nonproliferation Ontology Assessment Team Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Strasburg, Jana D.; Hohimer, Ryan E.

    2012-01-01

    Final Report for the NA22 Simulations, Algorithm and Modeling (SAM) Ontology Assessment Team's efforts from FY09-FY11. The Ontology Assessment Team began in May 2009 and concluded in September 2011. During this two-year time frame, the Ontology Assessment team had two objectives: (1) Assessing the utility of knowledge representation and semantic technologies for addressing nuclear nonproliferation challenges; and (2) Developing ontological support tools that would provide a framework for integrating across the Simulation, Algorithm and Modeling (SAM) program. The SAM Program was going through a large assessment and strategic planning effort during this time and as a result, the relative importance of these two objectives changed, altering the focus of the Ontology Assessment Team. In the end, the team conducted an assessment of the state of art, created an annotated bibliography, and developed a series of ontological support tools, demonstrations and presentations. A total of more than 35 individuals from 12 different research institutions participated in the Ontology Assessment Team. These included subject matter experts in several nuclear nonproliferation-related domains as well as experts in semantic technologies. Despite the diverse backgrounds and perspectives, the Ontology Assessment team functioned very well together and aspects could serve as a model for future inter-laboratory collaborations and working groups. While the team encountered several challenges and learned many lessons along the way, the Ontology Assessment effort was ultimately a success that led to several multi-lab research projects and opened up a new area of scientific exploration within the Office of Nuclear Nonproliferation and Verification.

  8. A Parsing Graph-based Algorithm for Ontology Mapping

    Institute of Scientific and Technical Information of China (English)

    WANG Zong-jiang; WANG Ying-lin; ZHANG Shen-sheng; DU Tao

    2009-01-01

    Ontology mapping is a critical problem for integrating the heterogeneous information sources. It can identify the elements corresponding to each other. At present, there are many ontology mapping algorithms, but most of them are bused on database schema. After analyzing the similarity and difference of ontology and schema, wepropose a parsing graph-based algorithm for ontology mapping. The ontology parsing graph (OP-graph) extends the general concept of graph, encodes logic relationship, and semantic information which the ontology contains into vertices and edges of the graph. Thus, the problem of ontology mapping is translated into a problem of finding the optimal match between the two OP-graphs. With the definition of a universal measure for comparing the entities of two ontoingies, we calculate the whole similarity between the two OP-graphs iteratively, until the optimal match is found. The results of experiments show that our algorithm is promising.

  9. Research on the complex network of the UNSPSC ontology

    Science.gov (United States)

    Xu, Yingying; Zou, Shengrong; Gu, Aihua; Wei, Li; Zhou, Ta

    The UNSPSC ontology mainly applies to the classification system of the e-business and governments buying the worldwide products and services, and supports the logic structure of classification of the products and services. In this paper, the related technologies of the complex network were applied to analyzing the structure of the ontology. The concept of the ontology was corresponding to the node of the complex network, and the relationship of the ontology concept was corresponding to the edge of the complex network. With existing methods of analysis and performance indicators in the complex network, analyzing the degree distribution and community of the ontology, and the research will help evaluate the concept of the ontology, classify the concept of the ontology and improve the efficiency of semantic matching.

  10. BiOSS: A system for biomedical ontology selection.

    Science.gov (United States)

    Martínez-Romero, Marcos; Vázquez-Naya, José M; Pereira, Javier; Pazos, Alejandro

    2014-04-01

    In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  11. Hybrid Reasoning with Rules and Ontologies

    Science.gov (United States)

    Drabent, Włodzimierz; Eiter, Thomas; Ianni, Giovambattista; Krennwallner, Thomas; Lukasiewicz, Thomas; Małuszyński, Jan

    The purpose of this chapter is to report on work that has been done in the REWERSE project concerning hybrid reasoning with rules and ontologies. Two major streams of work have been pursued within REWERSE. They start from the predominant semantics of non-monotonic rules in logic programming. The one stream was an extension of non-monotonic logic programs under answer set semantics, with query interfaces to external knowledge sources. The other stream, in the spirit of the mathcal{AL}-log approach of enhanced deductive databases, was an extension of Datalog (with the well-founded semantics, which is predominant in the database area). The former stream led to so-called non-monotonic dl-programs and hex-programs, and the latter stream to hybrid well-founded semantics. Further variants and derivations of the formalisms (like a well-founded semantics for dl-programs, respecting probabilistic knowledge, priorities, etc.) have been conceived.

  12. The UMLS Semantic Network and the Semantic Web.

    Science.gov (United States)

    Kashyap, Vipul

    2003-01-01

    The Unified Medical Language System is an extensive source of biomedical knowledge developed and maintained by the US National Library of Medicine (NLM) and is being currently used in a wide variety of biomedical applications. The Semantic Network, a component of the UMLS is a structured description of core biomedical knowledge consisting of well defined semantic types and relationships between them. We investigate the expressiveness of DAML+OIL, a markup language proposed for ontologies on the Semantic Web, for representing the knowledge contained in the Semantic Network. Requirements specific to the Semantic Network, such as polymorphic relationships and blocking relationship inheritance are discussed and approaches to represent these in DAML+OIL are presented. Finally, conclusions are presented along with a discussion of ongoing and future work.

  13. The Interaction of Lexical Semantics and Cohort Competition in Spoken Word Recognition: An fMRI Study

    Science.gov (United States)

    Zhuang, Jie; Randall, Billi; Stamatakis, Emmanuel A.; Marslen-Wilson, William D.; Tyler, Lorraine K.

    2011-01-01

    Spoken word recognition involves the activation of multiple word candidates on the basis of the initial speech input--the "cohort"--and selection among these competitors. Selection may be driven primarily by bottom-up acoustic-phonetic inputs or it may be modulated by other aspects of lexical representation, such as a word's meaning…

  14. Semantic annotation of medical images

    Science.gov (United States)

    Seifert, Sascha; Kelm, Michael; Moeller, Manuel; Mukherjee, Saikat; Cavallaro, Alexander; Huber, Martin; Comaniciu, Dorin

    2010-03-01

    Diagnosis and treatment planning for patients can be significantly improved by comparing with clinical images of other patients with similar anatomical and pathological characteristics. This requires the images to be annotated using common vocabulary from clinical ontologies. Current approaches to such annotation are typically manual, consuming extensive clinician time, and cannot be scaled to large amounts of imaging data in hospitals. On the other hand, automated image analysis while being very scalable do not leverage standardized semantics and thus cannot be used across specific applications. In our work, we describe an automated and context-sensitive workflow based on an image parsing system complemented by an ontology-based context-sensitive annotation tool. An unique characteristic of our framework is that it brings together the diverse paradigms of machine learning based image analysis and ontology based modeling for accurate and scalable semantic image annotation.

  15. Ontological backdrop

    DEFF Research Database (Denmark)

    Galle, Per

    2000-01-01

    In this report I keep track of ontological assumptions or implications of other OARs, introducing a system of categories and concepts that is compatible with them. The purpose was originally to keep terminology consistent throughout all OARs. However, the report also gives a condensed picture...... of the world view which underlies my current work on product modelling. It contains a justification of my view of concept exemplification, with lines traced back to Kant's work on epistemology....

  16. Masked priming and ERPs dissociate maturation of orthographic and semantic components of visual word recognition in children.

    Science.gov (United States)

    Eddy, Marianna D; Grainger, Jonathan; Holcomb, Phillip J; Mitra, Priya; Gabrieli, John D E

    2014-02-01

    This study examined the time-course of reading single words in children and adults using masked repetition priming and the recording of event-related potentials. The N250 and N400 repetition priming effects were used to characterize form- and meaning-level processing, respectively. Children had larger amplitude N250 effects than adults for both shorter and longer duration primes. Children did not differ from adults on the N400 effect. The difference on the N250 suggests that automaticity for form processing is still maturing in children relative to adults, while the lack of differentiation on the N400 effect suggests that meaning processing is relatively mature by late childhood. The overall similarity in the children's repetition priming effects to adults' effects is in line with theories of reading acquisition, according to which children rapidly transition to an orthographic strategy for fast access to semantic information from print. Copyright © 2013 Society for Psychophysiological Research.

  17. Geo-ontology design and its logic reasoning

    Science.gov (United States)

    Wang, Yandong; Dai, Jingjing; Sheng, Jizhen; Zhou, Kai; Gong, Jianya

    2007-06-01

    With the increasing application of geographic information system (GIS), GIS is faced with the difficulty of efficient management and comprehensive application of the spatial information from different resources and in different forms. In order to solve these problems, ontology is introduced into GIS field as a concept model which can represent object on semantic and knowledge level. Ontology not only can describe spatial data more easily understood by computers in semantic encoding method, but also can integrate geographical data from different sources and in different forms for reasoning. In this paper, a geo-ontology "GeographicalSpace" is built with Web Ontology Language (OWL) after analyzing the research and application of geo-ontology. A geo-ontology reasoning framework is put forward in which three layers are designed. The three layers are presentation layer, semantic service layer and spatial application server layer. By using the geo-ontology repository module and reasoning module in this framework, some more complex spatial location relationships in depth can be mined out. At last, an experiment is designed to demonstrate geo-ontology's ability to execute more intelligent query that can't be implemented in traditional GIS.

  18. Ontology Based Metadata Management for National Healthcare Data Dictionary

    Directory of Open Access Journals (Sweden)

    Yasemin Yüksek

    2012-02-01

    Full Text Available Ontology based metadata is based on ontologies that give formal semantics to information for content level. In this study, ontology based metadata management that intended the metadata modeling developed for National Health Data Dictionary (NHDD was proposed. NHDD is used as a reference to all health institutions in Turkey and it provides great contribution in terms of the terminology. The approach of the proposed ontology based metadata management was achieved by using modeling methodology of metadata requirements. This methodology includes determination of metadata beneficiaries, listing of metadata requirements for each beneficiary, identification of the source of metadata, categorizing of metadata and a metamodel building.

  19. Building ontologies with basic formal ontology

    CERN Document Server

    Arp, Robert; Spear, Andrew D.

    2015-01-01

    In the era of "big data," science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now u...

  20. Markov Chain Ontology Analysis (MCOA)

    Science.gov (United States)

    2012-01-01

    Background Biomedical ontologies have become an increasingly critical lens through which researchers analyze the genomic, clinical and bibliographic data that fuels scientific research. Of particular relevance are methods, such as enrichment analysis, that quantify the importance of ontology classes relative to a collection of domain data. Current analytical techniques, however, remain limited in their ability to handle many important types of structural complexity encountered in real biological systems including class overlaps, continuously valued data, inter-instance relationships, non-hierarchical relationships between classes, semantic distance and sparse data. Results In this paper, we describe a methodology called Markov Chain Ontology Analysis (MCOA) and illustrate its use through a MCOA-based enrichment analysis application based on a generative model of gene activation. MCOA models the classes in an ontology, the instances from an associated dataset and all directional inter-class, class-to-instance and inter-instance relationships as a single finite ergodic Markov chain. The adjusted transition probability matrix for this Markov chain enables the calculation of eigenvector values that quantify the importance of each ontology class relative to other classes and the associated data set members. On both controlled Gene Ontology (GO) data sets created with Escherichia coli, Drosophila melanogaster and Homo sapiens annotations and real gene expression data extracted from the Gene Expression Omnibus (GEO), the MCOA enrichment analysis approach provides the best performance of comparable state-of-the-art methods. Conclusion A methodology based on Markov chain models and network analytic metrics can help detect the relevant signal within large, highly interdependent and noisy data sets and, for applications such as enrichment analysis, has been shown to generate superior performance on both real and simulated data relative to existing state-of-the-art approaches

  1. Magpie: customizing users' experiences when browsing on the semantic web

    OpenAIRE

    Dzbor, Martin; Domingue, John; Motta, Enrico

    2004-01-01

    We describe several advanced functionalities of Magpie -- a tool that assists users with interpreting the web resources. Magpie is an extension to the Internet Explorer that automatically creates a semantic layer for web pages using a user-selected ontology. Semantic layers are annotations of a web page, with a set of applicable semantic services attached to the annotated items. We argue that the ability to generate different semantic layers for a web resource is vital to support the interpre...

  2. Semantic Roles and Grammatical Relations.

    Science.gov (United States)

    Van Valin, Robert D., Jr.

    The nature of semantic roles and grammatical relations are explored from the perspective of Role and Reference Grammar (RRG). It is proposed that unraveling the relational aspects of grammar involves the recognition that semantic roles fall into two types, thematic relations and macroroles, and that grammatical relations are not universal and are…

  3. Creativity Ontology

    OpenAIRE

    Jordanous, Anna; Keller, Bill

    2012-01-01

    A set of concepts which each contribute to the meaning of creativity. Each component/factor represents an aspect which is a constituent part of creative activity or thought. The full Collection of CreativityComponents is a collective definition of Creativity.\\ud \\ud Based on a SKOS organisation of knowledge. \\ud \\ud See Jordanous and Keller 2012 (Weaving Creativity into the Semantic Web) for further details.

  4. Geo-Ontologies Are Scale Dependent

    Science.gov (United States)

    Frank, A. U.

    2009-04-01

    Philosophers aim at a single ontology that describes "how the world is"; for information systems we aim only at ontologies that describe a conceptualization of reality (Guarino 1995; Gruber 2005). A conceptualization of the world implies a spatial and temporal scale: what are the phenomena, the objects and the speed of their change? Few articles (Reitsma et al. 2003) seem to address that an ontology is scale specific (but many articles indicate that ontologies are scale-free in another sense namely that they are scale free in the link densities between concepts). The scale in the conceptualization can be linked to the observation process. The extent of the support of the physical observation instrument and the sampling theorem indicate what level of detail we find in a dataset. These rules apply for remote sensing or sensor networks alike. An ontology of observations must include scale or level of detail, and concepts derived from observations should carry this relation forward. A simple example: in high resolution remote sensing image agricultural plots and roads between them are shown, at lower resolution, only the plots and not the roads are visible. This gives two ontologies, one with plots and roads, the other with plots only. Note that a neighborhood relation in the two different ontologies also yield different results. References Gruber, T. (2005). "TagOntology - a way to agree on the semantics of tagging data." Retrieved October 29, 2005., from http://tomgruber.org/writing/tagontology-tagcapm-talk.pdf. Guarino, N. (1995). "Formal Ontology, Conceptual Analysis and Knowledge Representation." International Journal of Human and Computer Studies. Special Issue on Formal Ontology, Conceptual Analysis and Knowledge Representation, edited by N. Guarino and R. Poli 43(5/6). Reitsma, F. and T. Bittner (2003). Process, Hierarchy, and Scale. Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information ScienceInternational Conference

  5. A Unified Semantic Framework for the description of assistive technologies.

    Science.gov (United States)

    Konstadinidou, Aggeliki; Kaklanis, Nikolaos; Votis, Konstantinos; Tzovaras, Dimitrios

    2015-01-01

    This paper presents the Semantic Alignment Tool, a unified, classified, ontological framework, for the description of assistive solutions that comprises information from different sources automatically. The Semantic Alignment Tool is a component of the Cloud4All/GPII infrastructure that enables users to add and/or modify descriptions of assistive technologies and align their specific settings with similar settings in an ontological model based on ISO 9999. The current work presents the interaction of the Semantic Alignment Tool with external sources that contain descriptions and metadata for Assistive Technologies (ATs) in order to achieve their synchronization in the same semantic model.

  6. Exploring biomedical ontology mappings with graph theory methods.

    Science.gov (United States)

    Kocbek, Simon; Kim, Jin-Dong

    2017-01-01

    In the era of semantic web, life science ontologies play an important role in tasks such as annotating biological objects, linking relevant data pieces, and verifying data consistency. Understanding ontology structures and overlapping ontologies is essential for tasks such as ontology reuse and development. We present an exploratory study where we examine structure and look for patterns in BioPortal, a comprehensive publicly available repository of live science ontologies. We report an analysis of biomedical ontology mapping data over time. We apply graph theory methods such as Modularity Analysis and Betweenness Centrality to analyse data gathered at five different time points. We identify communities, i.e., sets of overlapping ontologies, and define similar and closest communities. We demonstrate evolution of identified communities over time and identify core ontologies of the closest communities. We use BioPortal project and category data to measure community coherence. We also validate identified communities with their mutual mentions in scientific literature. With comparing mapping data gathered at five different time points, we identified similar and closest communities of overlapping ontologies, and demonstrated evolution of communities over time. Results showed that anatomy and health ontologies tend to form more isolated communities compared to other categories. We also showed that communities contain all or the majority of ontologies being used in narrower projects. In addition, we identified major changes in mapping data after migration to BioPortal Version 4.

  7. Improving ontologies by automatic reasoning and evaluation of logical definitions

    Directory of Open Access Journals (Sweden)

    Köhler Sebastian

    2011-10-01

    Full Text Available Abstract Background Ontologies are widely used to represent knowledge in biomedicine. Systematic approaches for detecting errors and disagreements are needed for large ontologies with hundreds or thousands of terms and semantic relationships. A recent approach of defining terms using logical definitions is now increasingly being adopted as a method for quality control as well as for facilitating interoperability and data integration. Results We show how automated reasoning over logical definitions of ontology terms can be used to improve ontology structure. We provide the Java software package GULO (Getting an Understanding of LOgical definitions, which allows fast and easy evaluation for any kind of logically decomposed ontology by generating a composite OWL ontology from appropriate subsets of the referenced ontologies and comparing the inferred relationships with the relationships asserted in the target ontology. As a case study we show how to use GULO to evaluate the logical definitions that have been developed for the Mammalian Phenotype Ontology (MPO. Conclusions Logical definitions of terms from biomedical ontologies represent an important resource for error and disagreement detection. GULO gives ontology curators a fast and simple tool for validation of their work.

  8. Gene Ontology

    Directory of Open Access Journals (Sweden)

    Gaston K. Mazandu

    2012-01-01

    Full Text Available The wide coverage and biological relevance of the Gene Ontology (GO, confirmed through its successful use in protein function prediction, have led to the growth in its popularity. In order to exploit the extent of biological knowledge that GO offers in describing genes or groups of genes, there is a need for an efficient, scalable similarity measure for GO terms and GO-annotated proteins. While several GO similarity measures exist, none adequately addresses all issues surrounding the design and usage of the ontology. We introduce a new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG, thus enabling the measurement of functional similarities between proteins based on their GO annotations. We assess the performance of this metric using a ROC analysis on human protein-protein interaction datasets and correlation coefficient analysis on the selected set of protein pairs from the CESSM online tool. This metric achieves good performance compared to the existing annotation-based GO measures. We used this new metric to assess functional similarity between orthologues, and show that it is effective at determining whether orthologues are annotated with similar functions and identifying cases where annotation is inconsistent between orthologues.

  9. Semantic models for adaptive interactive systems

    CERN Document Server

    Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

    2013-01-01

    Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

  10. Similarity Based Semantic Web Service Match

    Science.gov (United States)

    Peng, Hui; Niu, Wenjia; Huang, Ronghuai

    Semantic web service discovery aims at returning the most matching advertised services to the service requester by comparing the semantic of the request service with an advertised service. The semantic of a web service are described in terms of inputs, outputs, preconditions and results in Ontology Web Language for Service (OWL-S) which formalized by W3C. In this paper we proposed an algorithm to calculate the semantic similarity of two services by weighted averaging their inputs and outputs similarities. Case study and applications show the effectiveness of our algorithm in service match.

  11. Ontology-Based Search of Genomic Metadata.

    Science.gov (United States)

    Fernandez, Javier D; Lenzerini, Maurizio; Masseroli, Marco; Venco, Francesco; Ceri, Stefano

    2016-01-01

    The Encyclopedia of DNA Elements (ENCODE) is a huge and still expanding public repository of more than 4,000 experiments and 25,000 data files, assembled by a large international consortium since 2007; unknown biological knowledge can be extracted from these huge and largely unexplored data, leading to data-driven genomic, transcriptomic, and epigenomic discoveries. Yet, search of relevant datasets for knowledge discovery is limitedly supported: metadata describing ENCODE datasets are quite simple and incomplete, and not described by a coherent underlying ontology. Here, we show how to overcome this limitation, by adopting an ENCODE metadata searching approach which uses high-quality ontological knowledge and state-of-the-art indexing technologies. Specifically, we developed S.O.S. GeM (http://www.bioinformatics.deib.polimi.it/SOSGeM/), a system supporting effective semantic search and retrieval of ENCODE datasets. First, we constructed a Semantic Knowledge Base by starting with concepts extracted from ENCODE metadata, matched to and expanded on biomedical ontologies integrated in the well-established Unified Medical Language System. We prove that this inference method is sound and complete. Then, we leveraged the Semantic Knowledge Base to semantically search ENCODE data from arbitrary biologists' queries. This allows correctly finding more datasets than those extracted by a purely syntactic search, as supported by the other available systems. We empirically show the relevance of found datasets to the biologists' queries.

  12. Semantic representation of monogenean haptoral Bar image annotation.

    Science.gov (United States)

    Abu, Arpah; Susan, Lim Lee Hong; Sidhu, Amandeep Singh; Dhillon, Sarinder Kaur

    2013-02-12

    Digitised monogenean images are usually stored in file system directories in an unstructured manner. In this paper we propose a semantic representation of these images in the form of a Monogenean Haptoral Bar Image (MHBI) ontology, which are annotated with taxonomic classification, diagnostic hard part and image properties. The data we used are basically of the monogenean species found in fish, thus we built a simple Fish ontology to demonstrate how the host (fish) ontology can be linked to the MHBI ontology. This will enable linking of information from the monogenean ontology to the host species found in the fish ontology without changing the underlying schema for either of the ontologies. In this paper, we utilized the Taxonomic Data Working Group Life Sciences Identifier (TDWG LSID) vocabulary to represent our data and defined a new vocabulary which is specific for annotating monogenean haptoral bar images to develop the MHBI ontology and a merged MHBI-Fish ontologies. These ontologies are successfully evaluated using five criteria which are clarity, coherence, extendibility, ontology commitment and encoding bias. In this paper, we show that unstructured data can be represented in a structured form using semantics. In the process, we have come up with a new vocabulary for annotating the monogenean images with textual information. The proposed monogenean image ontology will form the basis of a monogenean knowledge base to assist researchers in retrieving information for their analysis.

  13. Two Language Models Using Chinese Semantic Parsing

    Institute of Scientific and Technical Information of China (English)

    LI Mingqin; WANG Xia; WANG Zuoying

    2006-01-01

    This paper presents two language models that utilize a Chinese semantic dependency parsing technique for speech recognition. The models are based on a representation of the Chinese semantic structure with dependency relations. A semantic dependency parser was described to automatically tag the semantic class for each word with 90.9% accuracy and parse the sentence semantic dependency structure with 75.8% accuracy. The Chinese semantic parsing technique was applied to structure language models to develop two language models, the semantic dependency model (SDM) and the headword trigram model (HTM). These language models were evaluated using Chinese speech recognition. The experiments show that both models outperform the word trigram model in terms of the Chinese character recognition error rate.

  14. Automatic Detection and Processing of Attributes Inconsistency for Fuzzy Ontologies Merging

    Directory of Open Access Journals (Sweden)

    Yonghong Luo

    2013-11-01

    Full Text Available Semantic fusion of multiple data sources and semantic interoperability between heterogeneous systems in distributed environment can be implemented through integrating multiple fuzzy local ontologies. However, ontology merging is one of the valid ways for ontology integration. In order to solve the problem of attributes inconsistency for concept mapping in fuzzy ontology merging system, we present an automatic detection algorithm of inconsistency for the range, number and membership grade of attributes between mapping concepts, and adopt corresponding processing strategy during the fuzzy ontologies merging according to the different types of attributes inconsistency. Experiment results show that with regard to merging accuracy, the fuzzy ontology merging system in which the automatic detection algorithm and processing strategy of attributes inconsistency is embedded is better than those traditional ontology merging systems like GLUE, PROMPT and Chimaera.    

  15. An Approach for Ontology Integration for Personalization with the Support of XML

    Directory of Open Access Journals (Sweden)

    S.Vigneshwari

    2014-01-01

    Full Text Available Ontological way of knowledge representation is very much useful to the semantic web. In the modernized computer era, there is a need of a special technique for personalization. XML plays an important role in information retrieval systems and XML being a common format for information interpretation, it will be easy to understand as well as easy to construct. In this paper, a framework has been proposed for personalizing the web using XML based ontologies. This framework needs integration between global ontology and locally generated ontology based on user profiles. The relevant concepts between both the ontologies are identified, grouped together and ranked. Finally, the generated ontologies are evaluated using standard datasets, based on their semantic structures. The clustered concepts and query pairs are being analyzed with varying threshold limits. In addition, the performance metrics show that the ontology based techniques show a good precision, recall values for the user given data, when compared to text-based approaches.

  16. OntoELAN: An Ontology-based Linguistic Multimedia Annotator

    CERN Document Server

    Chebotko, Artem; Lu, Shiyong; Fotouhi, Farshad; Aristar, Anthony; Brugman, Hennie; Klassmann, Alexander; Sloetjes, Han; Russel, Albert; Wittenburg, Peter

    2009-01-01

    Despite its scientific, political, and practical value, comprehensive information about human languages, in all their variety and complexity, is not readily obtainable and searchable. One reason is that many language data are collected as audio and video recordings which imposes a challenge to document indexing and retrieval. Annotation of multimedia data provides an opportunity for making the semantics explicit and facilitates the searching of multimedia documents. We have developed OntoELAN, an ontology-based linguistic multimedia annotator that features: (1) support for loading and displaying ontologies specified in OWL; (2) creation of a language profile, which allows a user to choose a subset of terms from an ontology and conveniently rename them if needed; (3) creation of ontological tiers, which can be annotated with profile terms and, therefore, corresponding ontological terms; and (4) saving annotations in the XML format as Multimedia Ontology class instances and, linked to them, class instances of o...

  17. Unsupervised and self-mapping category formation and semantic object recognition for mobile robot vision used in an actual environment

    Science.gov (United States)

    Madokoro, H.; Tsukada, M.; Sato, K.

    2013-07-01

    This paper presents an unsupervised learning-based object category formation and recognition method for mobile robot vision. Our method has the following features: detection of feature points and description of features using a scale-invariant feature transform (SIFT), selection of target feature points using one class support vector machines (OC-SVMs), generation of visual words using self-organizing maps (SOMs), formation of labels using adaptive resonance theory 2 (ART-2), and creation and classification of categories on a category map of counter propagation networks (CPNs) for visualizing spatial relations between categories. Classification results of dynamic images using time-series images obtained using two different-size robots and according to movements respectively demonstrate that our method can visualize spatial relations of categories while maintaining time-series characteristics. Moreover, we emphasize the effectiveness of our method for category formation of appearance changes of objects.

  18. Using AberOWL for fast and scalable reasoning over BioPortal ontologies

    KAUST Repository

    Slater, Luke

    2016-08-08

    Background: Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most other tools utilizing ontologies, either provide access to ontologies without use of automated reasoning, or limit the number of ontologies for which automated reasoning-based access is provided. Methods: We apply the AberOWL infrastructure to provide automated reasoning-based access to all accessible and consistent ontologies in BioPortal (368 ontologies). We perform an extensive performance evaluation to determine query times, both for queries of different complexity and for queries that are performed in parallel over the ontologies. Results and conclusions: We demonstrate that, with the exception of a few ontologies, even complex and parallel queries can now be answered in milliseconds, therefore allowing automated reasoning to be used on a large scale, to run in parallel, and with rapid response times.

  19. Developing an Ontology for Ocean Biogeochemistry Data

    Science.gov (United States)

    Chandler, C. L.; Allison, M. D.; Groman, R. C.; West, P.; Zednik, S.; Maffei, A. R.

    2010-12-01

    Semantic Web technologies offer great promise for enabling new and better scientific research. However, significant challenges must be met before the promise of the Semantic Web can be realized for a discipline as diverse as oceanography. Evolving expectations for open access to research data combined with the complexity of global ecosystem science research themes present a significant challenge, and one that is best met through an informatics approach. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is funded by the National Science Foundation Division of Ocean Sciences to work with ocean biogeochemistry researchers to improve access to data resulting from their respective programs. In an effort to improve data access, BCO-DMO staff members are collaborating with researchers from the Tetherless World Constellation (Rensselaer Polytechnic Institute) to develop an ontology that formally describes the concepts and relationships in the data managed by the BCO-DMO. The project required transforming a legacy system of human-readable, flat files of metadata to well-ordered controlled vocabularies to a fully developed ontology. To improve semantic interoperability, terms from the BCO-DMO controlled vocabularies are being mapped to controlled vocabulary terms adopted by other oceanographic data management organizations. While the entire process has proven to be difficult, time-consuming and labor-intensive, the work has been rewarding and is a necessary prerequisite for the eventual incorporation of Semantic Web tools. From the beginning of the project, development of the ontology has been guided by a use case based approach. The use cases were derived from data access related requests received from members of the research community served by the BCO-DMO. The resultant ontology satisfies the requirements of the use cases and reflects the information stored in the metadata database. The BCO-DMO metadata database currently contains information that

  20. Development of National Map ontologies for organization and orchestration of hydrologic observations

    Science.gov (United States)

    Lieberman, J. E.

    2014-12-01

    Feature layers in the National Map program (TNM) are a fundamental context for much of the data collection and analysis conducted by the USGS and other governmental and nongovernmental organizations. Their computational usefulness, though, has been constrained by the lack of formal relationships besides superposition between TNM layers, as well as limited means of representing how TNM datasets relate to additional attributes, datasets, and activities. In the field of Geospatial Information Science, there has been a growing recognition of the value of semantic representation and technology for addressing these limitations, particularly in the face of burgeoning information volume and heterogeneity. Fundamental to this approach is the development of formal ontologies for concepts related to that information that can be processed computationally to enhance creation and discovery of new geospatial knowledge. They offer a means of making much of the presently innate knowledge about relationships in and between TNM features accessible for machine processing and distributed computation.A full and comprehensive ontology of all knowledge represented by TNM features is still impractical. The work reported here involves elaboration and integration of a number of small ontology design patterns (ODP's) that represent limited, discrete, but commonly accepted and broadly applicable physical theories for the behavior of TNM features representing surface water bodies and landscape surfaces and the connections between them. These ontology components are validated through use in applications for discovery and aggregation of water science observational data associated with National Hydrography Data features, features from the National Elevation Dataset (NED) and Water Boundary Dataset (WBD) that constrain water occurrence in the continental US. These applications emphasize workflows which are difficult or impossible to automate using existing data structures. Evaluation of the