Query Expansion: Is It Necessary In Textual Case-Based Reasoning ...

African Journals Online (AJOL)

Query expansion (QE) is the process of transforming a seed query to improve retrieval performance in information retrieval operations. It is often intended to overcome a vocabulary mismatch between the query and the document collection. Query expansion is known to improve retrieval effectiveness of some information ...

Retrieval of diagnostic and treatment studies for clinical use through PubMed and PubMed's Clinical Queries filters.

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Lokker, Cynthia; Haynes, R Brian; Wilczynski, Nancy L; McKibbon, K Ann; Walter, Stephen D

2011-01-01

Clinical Queries filters were developed to improve the retrieval of high-quality studies in searches on clinical matters. The study objective was to determine the yield of relevant citations and physician satisfaction while searching for diagnostic and treatment studies using the Clinical Queries page of PubMed compared with searching PubMed without these filters. Forty practicing physicians, presented with standardized treatment and diagnosis questions and one question of their choosing, entered search terms which were processed in a random, blinded fashion through PubMed alone and PubMed Clinical Queries. Participants rated search retrievals for applicability to the question at hand and satisfaction. For treatment, the primary outcome of retrieval of relevant articles was not significantly different between the groups, but a higher proportion of articles from the Clinical Queries searches met methodologic criteria (p=0.049), and more articles were published in core internal medicine journals (p=0.056). For diagnosis, the filtered results returned more relevant articles (p=0.031) and fewer irrelevant articles (overall retrieval less, p=0.023); participants needed to screen fewer articles before arriving at the first relevant citation (p<0.05). Relevance was also influenced by content terms used by participants in searching. Participants varied greatly in their search performance. Clinical Queries filtered searches returned more high-quality studies, though the retrieval of relevant articles was only statistically different between the groups for diagnosis questions. Retrieving clinically important research studies from Medline is a challenging task for physicians. Methodological search filters can improve search retrieval.

The effect of query complexity on Web searching results

Directory of Open Access Journals (Sweden)

B.J. Jansen

2000-01-01

Full Text Available This paper presents findings from a study of the effects of query structure on retrieval by Web search services. Fifteen queries were selected from the transaction log of a major Web search service in simple query form with no advanced operators (e.g., Boolean operators, phrase operators, etc. and submitted to 5 major search engines - Alta Vista, Excite, FAST Search, Infoseek, and Northern Light. The results from these queries became the baseline data. The original 15 queries were then modified using the various search operators supported by each of the 5 search engines for a total of 210 queries. Each of these 210 queries was also submitted to the applicable search service. The results obtained were then compared to the baseline results. A total of 2,768 search results were returned by the set of all queries. In general, increasing the complexity of the queries had little effect on the results with a greater than 70% overlap in results, on average. Implications for the design of Web search services and directions for future research are discussed.

Sketch-Based Spatial Queries for the Retrieval of Human Locomotion Patterns in Smart Environments

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Gamhewage C. de Silva

2009-01-01

Full Text Available A system for retrieving video sequences created by tracking humans in a smart environment, by using spatial queries, is presented. Sketches made with a pointing device on the floor layout of the environment are used to form queries corresponding to locomotion patterns. The sketches are analyzed to identify the type of the query. Directional search algorithms based on the minimum distance between points are applied for finding the best matches to the sketch. The results are ranked according to the similarity and presented to the user. The system was developed in two stages. An initial version of the system was implemented and evaluated by conducting a user study. Modifications were made where appropriate, according to the results and the feedback, to make the system more accurate and usable. We present the details of the initial system, the user study and the results, and the modifications thus made. The overall accuracy of retrieval for the initial system was approximately 93%, when tested on a collection of data from a real-life experiment. This is improved to approximately 97% after the modifications. The user interaction strategy and the search algorithms are usable in any environment for automated retrieval of locomotion patterns. The subjects who evaluated the system found it easy to learn and use. Their comments included several prospective applications for the user interaction strategy, providing valuable insight for future directions.

Recommending Multidimensional Queries

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Giacometti, Arnaud; Marcel, Patrick; Negre, Elsa

Interactive analysis of datacube, in which a user navigates a cube by launching a sequence of queries is often tedious since the user may have no idea of what the forthcoming query should be in his current analysis. To better support this process we propose in this paper to apply a Collaborative Work approach that leverages former explorations of the cube to recommend OLAP queries. The system that we have developed adapts Approximate String Matching, a technique popular in Information Retrieval, to match the current analysis with the former explorations and help suggesting a query to the user. Our approach has been implemented with the open source Mondrian OLAP server to recommend MDX queries and we have carried out some preliminary experiments that show its efficiency for generating effective query recommendations.

Semantic-based surveillance video retrieval.

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Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve

2007-04-01

Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.

Effects of Diacritics on Web Search Engines’ Performance for Retrieval of Yoruba Documents

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Toluwase Victor Asubiaro

2014-06-01

Full Text Available This paper aims to find out the possible effect of the use or nonuse of diacritics in Yoruba search queries on the performance of major search engines, AOL, Bing, Google and Yahoo!, in retrieving documents. 30 Yoruba queries created from the most searched keywords from Nigeria on Google search logs were submitted to the search engines. The search queries were posed to the search engines without diacritics and then with diacritics. All of the search engines retrieved more sites in response to the queries without diacritics. Also, they all retrieved more precise results for queries without diacritics. The search engines also answered more queries without diacritics. There was no significant difference in the precision values of any two of the four search engines for diacritized and undiacritized queries. There was a significant difference in the effectiveness of AOL and Yahoo when diacritics were applied and when they were not applied. The findings of the study indicate that the search engines do not find a relationship between the diacritized Yoruba words and the undiacritized versions. Therefore, there is a need for search engines to add normalization steps to pre-process Yoruba queries and indexes. This study concentrates on a problem with search engines that has not been previously investigated.

Retrieving top-k prestige-based relevant spatial web objects

DEFF Research Database (Denmark)

Cao, Xin; Cong, Gao; Jensen, Christian S.

2010-01-01

The location-aware keyword query returns ranked objects that are near a query location and that have textual descriptions that match query keywords. This query occurs inherently in many types of mobile and traditional web services and applications, e.g., Yellow Pages and Maps services. Previous...... of prestige-based relevance to capture both the textual relevance of an object to a query and the effects of nearby objects. Based on this, a new type of query, the Location-aware top-k Prestige-based Text retrieval (LkPT) query, is proposed that retrieves the top-k spatial web objects ranked according...... to both prestige-based relevance and location proximity. We propose two algorithms that compute LkPT queries. Empirical studies with real-world spatial data demonstrate that LkPT queries are more effective in retrieving web objects than a previous approach that does not consider the effects of nearby...

Path-based Queries on Trajectory Data

DEFF Research Database (Denmark)

Krogh, Benjamin Bjerre; Pelekis, Nikos; Theodoridis, Yannis

2014-01-01

In traffic research, management, and planning a number of path-based analyses are heavily used, e.g., for computing turn-times, evaluating green waves, or studying traffic flow. These analyses require retrieving the trajectories that follow the full path being analyzed. Existing path queries cannot...... sufficiently support such path-based analyses because they retrieve all trajectories that touch any edge in the path. In this paper, we define and formalize the strict path query. This is a novel query type tailored to support path-based analysis, where trajectories must follow all edges in the path...... a specific path by only retrieving data from the first and last edge in the path. To correctly answer strict path queries existing network-constrained trajectory indexes must retrieve data from all edges in the path. An extensive performance study of NETTRA using a very large real-world trajectory data set...

User's manual for QUERY: a computer program for retrieval of environmental data

Energy Technology Data Exchange (ETDEWEB)

Nyholm, R.A.

1979-03-06

QUERY is a computer program used for the retrieval of environmental data. The code was developed in support of the Imperial Valley Environmental Project of the Environmental Sciences division at Lawrence Livermore Laboratory to handle a multitude of environmentally related information. The program can run in either an interactive mode or production mode to retrieve these data. In either case, the user specifies a set of search constraints and then proceeds to select an output format from a menu of output options or to specify the output format according to his immediate needs. Basic data statistics can be requested. Merging of disparate data bases and subfile extraction are elementary.

Probabilistic and machine learning-based retrieval approaches for biomedical dataset retrieval

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Karisani, Payam; Qin, Zhaohui S; Agichtein, Eugene

2018-01-01

Abstract The bioCADDIE dataset retrieval challenge brought together different approaches to retrieval of biomedical datasets relevant to a user’s query, expressed as a text description of a needed dataset. We describe experiments in applying a data-driven, machine learning-based approach to biomedical dataset retrieval as part of this challenge. We report on a series of experiments carried out to evaluate the performance of both probabilistic and machine learning-driven techniques from information retrieval, as applied to this challenge. Our experiments with probabilistic information retrieval methods, such as query term weight optimization, automatic query expansion and simulated user relevance feedback, demonstrate that automatically boosting the weights of important keywords in a verbose query is more effective than other methods. We also show that although there is a rich space of potential representations and features available in this domain, machine learning-based re-ranking models are not able to improve on probabilistic information retrieval techniques with the currently available training data. The models and algorithms presented in this paper can serve as a viable implementation of a search engine to provide access to biomedical datasets. The retrieval performance is expected to be further improved by using additional training data that is created by expert annotation, or gathered through usage logs, clicks and other processes during natural operation of the system. Database URL: https://github.com/emory-irlab/biocaddie

Superfund Query

Data.gov (United States)

U.S. Environmental Protection Agency — The Superfund Query allows users to retrieve data from the Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) database.

Comparison of the effectiveness of alternative feature sets in shape retrieval of multicomponent images

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Eakins, John P.; Edwards, Jonathan D.; Riley, K. Jonathan; Rosin, Paul L.

2001-01-01

Many different kinds of features have been used as the basis for shape retrieval from image databases. This paper investigates the relative effectiveness of several types of global shape feature, both singly and in combination. The features compared include well-established descriptors such as Fourier coefficients and moment invariants, as well as recently-proposed measures of triangularity and ellipticity. Experiments were conducted within the framework of the ARTISAN shape retrieval system, and retrieval effectiveness assessed on a database of over 10,000 images, using 24 queries and associated ground truth supplied by the UK Patent Office . Our experiments revealed only minor differences in retrieval effectiveness between different measures, suggesting that a wide variety of shape feature combinations can provide adequate discriminating power for effective shape retrieval in multi-component image collections such as trademark registries. Marked differences between measures were observed for some individual queries, suggesting that there could be considerable scope for improving retrieval effectiveness by providing users with an improved framework for searching multi-dimensional feature space.

Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining

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S. Sadesh

2015-01-01

Full Text Available Web with tremendous volume of information retrieves result for user related queries. With the rapid growth of web page recommendation, results retrieved based on data mining techniques did not offer higher performance filtering rate because relationships between user profile and queries were not analyzed in an extensive manner. At the same time, existing user profile based prediction in web data mining is not exhaustive in producing personalized result rate. To improve the query result rate on dynamics of user behavior over time, Hamilton Filtered Regime Switching User Query Probability (HFRS-UQP framework is proposed. HFRS-UQP framework is split into two processes, where filtering and switching are carried out. The data mining based filtering in our research work uses the Hamilton Filtering framework to filter user result based on personalized information on automatic updated profiles through search engine. Maximized result is fetched, that is, filtered out with respect to user behavior profiles. The switching performs accurate filtering updated profiles using regime switching. The updating in profile change (i.e., switches regime in HFRS-UQP framework identifies the second- and higher-order association of query result on the updated profiles. Experiment is conducted on factors such as personalized information search retrieval rate, filtering efficiency, and precision ratio.

A Revisit of Query Expansion with Different Semantic Levels

DEFF Research Database (Denmark)

Zhang, Ce; Cui, Bin; Cong, Gao

2009-01-01

Query expansion has received extensive attention in information retrieval community. Although semantic based query expansion appears to be promising in improving retrieval performance, previous research has shown that it cannot consistently improve retrieval performance. It is a tricky problem to...

Searching for rare diseases in PubMed: a blind comparison of Orphanet expert query and query based on terminological knowledge.

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Griffon, N; Schuers, M; Dhombres, F; Merabti, T; Kerdelhué, G; Rollin, L; Darmoni, S J

2016-08-02

Despite international initiatives like Orphanet, it remains difficult to find up-to-date information about rare diseases. The aim of this study is to propose an exhaustive set of queries for PubMed based on terminological knowledge and to evaluate it versus the queries based on expertise provided by the most frequently used resource in Europe: Orphanet. Four rare disease terminologies (MeSH, OMIM, HPO and HRDO) were manually mapped to each other permitting the automatic creation of expended terminological queries for rare diseases. For 30 rare diseases, 30 citations retrieved by Orphanet expert query and/or query based on terminological knowledge were assessed for relevance by two independent reviewers unaware of the query's origin. An adjudication procedure was used to resolve any discrepancy. Precision, relative recall and F-measure were all computed. For each Orphanet rare disease (n = 8982), there was a corresponding terminological query, in contrast with only 2284 queries provided by Orphanet. Only 553 citations were evaluated due to queries with 0 or only a few hits. There were no significant differences between the Orpha query and terminological query in terms of precision, respectively 0.61 vs 0.52 (p = 0.13). Nevertheless, terminological queries retrieved more citations more often than Orpha queries (0.57 vs. 0.33; p = 0.01). Interestingly, Orpha queries seemed to retrieve older citations than terminological queries (p < 0.0001). The terminological queries proposed in this study are now currently available for all rare diseases. They may be a useful tool for both precision or recall oriented literature search.

Relevance of useful visual words in object retrieval

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Qi, Siyuan; Luo, Yupin

2013-07-01

The most popular methods in object retrieval are almost based on bag-of-words(BOW) which is both effective and efficient. In this paper we present a method use the relations between words of the vocabulary to improve the retrieval performance based on the BOW framework. In basic BOW retrieval framework, only a few words of the vocabulary is useful for retrieval, which are spatial consistent in images. We introduce a method to useful select useful words and build a relevance between these words. We combine useful relevance with basic BOW framework and query expansion as well. The useful relevance is able to discover latent related words which is not exist in the query image, so that we can get a more accurate vector model for retrieval. Combined with query expansion method, the retrieval performance are better and fewer time cost.

Result Diversification Based on Query-Specific Cluster Ranking

NARCIS (Netherlands)

J. He (Jiyin); E. Meij; M. de Rijke (Maarten)

2011-01-01

htmlabstractResult diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking,

Video Retrieval Berdasarkan Teks dan Gambar

Directory of Open Access Journals (Sweden)

Rahmi Hidayati

2013-01-01

Abstract Retrieval video has been used to search a video based on the query entered by user which were text and image. This system could increase the searching ability on video browsing and expected to reduce the video’s retrieval time. The research purposes were designing and creating a software application of retrieval video based on the text and image on the video. The index process for the text is tokenizing, filtering (stopword, stemming. The results of stemming to saved in the text index table. Index process for the image is to create an image color histogram and compute the mean and standard deviation at each primary color red, green and blue (RGB of each image. The results of feature extraction is stored in the image table The process of video retrieval using the query text, images or both. To text query system to process the text query by looking at the text index tables. If there is a text query on the index table system will display information of the video according to the text query. To image query system to process the image query by finding the value of the feature extraction means red, green means, means blue, red standard deviation, standard deviation and standard deviation of blue green. If the value of the six features extracted query image on the index table image will display the video information system according to the query image. To query text and query images, the system will display the video information if the query text and query images have a relationship that is query text and query image has the same film title.   Keywords—  video, index, retrieval, text, image

Analysis of queries sent to PubMed at the point of care: Observation of search behaviour in a medical teaching hospital

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Hoogendam, Arjen; Stalenhoef, Anton FH; Robbé, Pieter F de Vries; Overbeke, A John PM

2008-01-01

Background The use of PubMed to answer daily medical care questions is limited because it is challenging to retrieve a small set of relevant articles and time is restricted. Knowing what aspects of queries are likely to retrieve relevant articles can increase the effectiveness of PubMed searches. The objectives of our study were to identify queries that are likely to retrieve relevant articles by relating PubMed search techniques and tools to the number of articles retrieved and the selection of articles for further reading. Methods This was a prospective observational study of queries regarding patient-related problems sent to PubMed by residents and internists in internal medicine working in an Academic Medical Centre. We analyzed queries, search results, query tools (Mesh, Limits, wildcards, operators), selection of abstract and full-text for further reading, using a portal that mimics PubMed. Results PubMed was used to solve 1121 patient-related problems, resulting in 3205 distinct queries. Abstracts were viewed in 999 (31%) of these queries, and in 126 (39%) of 321 queries using query tools. The average term count per query was 2.5. Abstracts were selected in more than 40% of queries using four or five terms, increasing to 63% if the use of four or five terms yielded 2–161 articles. Conclusion Queries sent to PubMed by physicians at our hospital during daily medical care contain fewer than three terms. Queries using four to five terms, retrieving less than 161 article titles, are most likely to result in abstract viewing. PubMed search tools are used infrequently by our population and are less effective than the use of four or five terms. Methods to facilitate the formulation of precise queries, using more relevant terms, should be the focus of education and research. PMID:18816391

Result diversification based on query-specific cluster ranking

NARCIS (Netherlands)

He, J.; Meij, E.; de Rijke, M.

2011-01-01

Result diversification is a retrieval strategy for dealing with ambiguous or multi-faceted queries by providing documents that cover as many facets of the query as possible. We propose a result diversification framework based on query-specific clustering and cluster ranking, in which diversification

Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

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Suzuki Motoyuki

2009-01-01

Full Text Available Abstract We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the "query relevance." Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

Automatic Query Generation and Query Relevance Measurement for Unsupervised Language Model Adaptation of Speech Recognition

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Akinori Ito

2009-01-01

Full Text Available We are developing a method of Web-based unsupervised language model adaptation for recognition of spoken documents. The proposed method chooses keywords from the preliminary recognition result and retrieves Web documents using the chosen keywords. A problem is that the selected keywords tend to contain misrecognized words. The proposed method introduces two new ideas for avoiding the effects of keywords derived from misrecognized words. The first idea is to compose multiple queries from selected keyword candidates so that the misrecognized words and correct words do not fall into one query. The second idea is that the number of Web documents downloaded for each query is determined according to the “query relevance.” Combining these two ideas, we can alleviate bad effect of misrecognized keywords by decreasing the number of downloaded Web documents from queries that contain misrecognized keywords. Finally, we examine a method of determining the number of iterative adaptations based on the recognition likelihood. Experiments have shown that the proposed stopping criterion can determine almost the optimum number of iterations. In the final experiment, the word accuracy without adaptation (55.29% was improved to 60.38%, which was 1.13 point better than the result of the conventional unsupervised adaptation method (59.25%.

Exploiting External Collections for Query Expansion

NARCIS (Netherlands)

Weerkamp, W.; Balog, K.; de Rijke, M.

2012-01-01

A persisting challenge in the field of information retrieval is the vocabulary mismatch between a user’s information need and the relevant documents. One way of addressing this issue is to apply query modeling: to add terms to the original query and reweigh the terms. In social media, where

Private information retrieval

CERN Document Server

Yi, Xun; Bertino, Elisa

2013-01-01

This book deals with Private Information Retrieval (PIR), a technique allowing a user to retrieve an element from a server in possession of a database without revealing to the server which element is retrieved. PIR has been widely applied to protect the privacy of the user in querying a service provider on the Internet. For example, by PIR, one can query a location-based service provider about the nearest car park without revealing his location to the server.The first PIR approach was introduced by Chor, Goldreich, Kushilevitz and Sudan in 1995 in a multi-server setting, where the user retriev

Collective spatial keyword querying

DEFF Research Database (Denmark)

Cao, Xin; Cong, Gao; Jensen, Christian S.

2011-01-01

With the proliferation of geo-positioning and geo-tagging, spatial web objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However, the quer......With the proliferation of geo-positioning and geo-tagging, spatial web objects that possess both a geographical location and a textual description are gaining in prevalence, and spatial keyword queries that exploit both location and textual description are gaining in prominence. However......, the queries studied so far generally focus on finding individual objects that each satisfy a query rather than finding groups of objects where the objects in a group collectively satisfy a query. We define the problem of retrieving a group of spatial web objects such that the group's keywords cover the query......'s keywords and such that objects are nearest to the query location and have the lowest inter-object distances. Specifically, we study two variants of this problem, both of which are NP-complete. We devise exact solutions as well as approximate solutions with provable approximation bounds to the problems. We...

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.

Science.gov (United States)

Hanauer, David A; Wu, Danny T Y; Yang, Lei; Mei, Qiaozhu; Murkowski-Steffy, Katherine B; Vydiswaran, V G Vinod; Zheng, Kai

2017-03-01

The utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs). The query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model. The search engine's performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks. Challenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge. Published by Elsevier Inc.

An Approach to Retrieval of OCR Degraded Text

Directory of Open Access Journals (Sweden)

Yuen-Hsien Tseng

1998-12-01

Full Text Available The major problem with retrieval of OCR text is the unpredictable distortion of characters due to recognition errors. Because users have no ideas of such distortion, the terms they query can hardly match the terms stored in the OCR text exactly. Thus retrieval effectiveness is significantly reduced , especially for low-quality input. To reduce the losses from retrieving such noisy OCR text, a fault-tolerant retrieval strategy based on automatic keyword extraction and fuzzy matching is proposed. In this strategy, terms, correct or not, and their term frequencies are extracted from the noisy text and presented for browsing and selection in response to users' initial queries , With theunderstanding of the real terms stored in the noisy text and of their estimated frequency distributions, users may then choose appropriate terms for a more effective searching, A text retrieval system based on this strategy has been built. Examples to show the effectiveness are demonstrated. Finally, some OCR issues for further enhancingretrieval effectiveness are discussed.

QCS: a system for querying, clustering and summarizing documents.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M.; Schlesinger, Judith D. (Center for Computing Sciences, Bowie, MD); O' Leary, Dianne P. (University of Maryland, College Park, MD); Conroy, John M. (Center for Computing Sciences, Bowie, MD)

2006-10-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test sets from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence 'trimming', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of the design

QCS : a system for querying, clustering, and summarizing documents.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M.

2006-08-01

Information retrieval systems consist of many complicated components. Research and development of such systems is often hampered by the difficulty in evaluating how each particular component would behave across multiple systems. We present a novel hybrid information retrieval system--the Query, Cluster, Summarize (QCS) system--which is portable, modular, and permits experimentation with different instantiations of each of the constituent text analysis components. Most importantly, the combination of the three types of components in the QCS design improves retrievals by providing users more focused information organized by topic. We demonstrate the improved performance by a series of experiments using standard test sets from the Document Understanding Conferences (DUC) along with the best known automatic metric for summarization system evaluation, ROUGE. Although the DUC data and evaluations were originally designed to test multidocument summarization, we developed a framework to extend it to the task of evaluation for each of the three components: query, clustering, and summarization. Under this framework, we then demonstrate that the QCS system (end-to-end) achieves performance as good as or better than the best summarization engines. Given a query, QCS retrieves relevant documents, separates the retrieved documents into topic clusters, and creates a single summary for each cluster. In the current implementation, Latent Semantic Indexing is used for retrieval, generalized spherical k-means is used for the document clustering, and a method coupling sentence ''trimming'', and a hidden Markov model, followed by a pivoted QR decomposition, is used to create a single extract summary for each cluster. The user interface is designed to provide access to detailed information in a compact and useful format. Our system demonstrates the feasibility of assembling an effective IR system from existing software libraries, the usefulness of the modularity of

VMQL: A Visual Language for Ad-Hoc Model Querying

DEFF Research Database (Denmark)

Störrle, Harald

2011-01-01

In large scale model based development, analysis level models are more like knowledge bases than engineering artifacts. Their effectiveness depends, to a large degree, on the ability of domain experts to retrieve information from them ad hoc. For large scale models, however, existing query...

Efficient view based 3-D object retrieval using Hidden Markov Model

Science.gov (United States)

Jain, Yogendra Kumar; Singh, Roshan Kumar

2013-12-01

Recent research effort has been dedicated to view based 3-D object retrieval, because of highly discriminative property of 3-D object and has multi view representation. The state-of-art method is highly depending on their own camera array setting for capturing views of 3-D object and use complex Zernike descriptor, HAC for representative view selection which limit their practical application and make it inefficient for retrieval. Therefore, an efficient and effective algorithm is required for 3-D Object Retrieval. In order to move toward a general framework for efficient 3-D object retrieval which is independent of camera array setting and avoidance of representative view selection, we propose an Efficient View Based 3-D Object Retrieval (EVBOR) method using Hidden Markov Model (HMM). In this framework, each object is represented by independent set of view, which means views are captured from any direction without any camera array restriction. In this, views are clustered (including query view) to generate the view cluster, which is then used to build the query model with HMM. In our proposed method, HMM is used in twofold: in the training (i.e. HMM estimate) and in the retrieval (i.e. HMM decode). The query model is trained by using these view clusters. The EVBOR query model is worked on the basis of query model combining with HMM. The proposed approach remove statically camera array setting for view capturing and can be apply for any 3-D object database to retrieve 3-D object efficiently and effectively. Experimental results demonstrate that the proposed scheme has shown better performance than existing methods. [Figure not available: see fulltext.

Discovering biomedical semantic relations in PubMed queries for information retrieval and database curation.

Science.gov (United States)

Huang, Chung-Chi; Lu, Zhiyong

2016-01-01

Identifying relevant papers from the literature is a common task in biocuration. Most current biomedical literature search systems primarily rely on matching user keywords. Semantic search, on the other hand, seeks to improve search accuracy by understanding the entities and contextual relations in user keywords. However, past research has mostly focused on semantically identifying biological entities (e.g. chemicals, diseases and genes) with little effort on discovering semantic relations. In this work, we aim to discover biomedical semantic relations in PubMed queries in an automated and unsupervised fashion. Specifically, we focus on extracting and understanding the contextual information (or context patterns) that is used by PubMed users to represent semantic relations between entities such as 'CHEMICAL-1 compared to CHEMICAL-2' With the advances in automatic named entity recognition, we first tag entities in PubMed queries and then use tagged entities as knowledge to recognize pattern semantics. More specifically, we transform PubMed queries into context patterns involving participating entities, which are subsequently projected to latent topics via latent semantic analysis (LSA) to avoid the data sparseness and specificity issues. Finally, we mine semantically similar contextual patterns or semantic relations based on LSA topic distributions. Our two separate evaluation experiments of chemical-chemical (CC) and chemical-disease (CD) relations show that the proposed approach significantly outperforms a baseline method, which simply measures pattern semantics by similarity in participating entities. The highest performance achieved by our approach is nearly 0.9 and 0.85 respectively for the CC and CD task when compared against the ground truth in terms of normalized discounted cumulative gain (nDCG), a standard measure of ranking quality. These results suggest that our approach can effectively identify and return related semantic patterns in a ranked order

Towards Automatic Improvement of Patient Queries in Health Retrieval Systems

Directory of Open Access Journals (Sweden)

Nesrine KSENTINI

2016-07-01

Full Text Available With the adoption of health information technology for clinical health, e-health is becoming usual practice today. Users of this technology find it difficult to seek information relevant to their needs due to the increasing amount of the clinical and medical data on the web, and the lack of knowledge of medical jargon. In this regards, a method is described to improve user's needs by automatically adding new related terms to their queries which appear in the same context of the original query in order to improve final search results. This method is based on the assessment of semantic relationships defined by a proposed statistical method between a set of terms or keywords. Experiments were performed on CLEF-eHealth-2015 database and the obtained results show the effectiveness of our proposed method.

How Do Children Reformulate Their Search Queries?

Science.gov (United States)

Rutter, Sophie; Ford, Nigel; Clough, Paul

2015-01-01

Introduction: This paper investigates techniques used by children in year 4 (age eight to nine) of a UK primary school to reformulate their queries, and how they use information retrieval systems to support query reformulation. Method: An in-depth study analysing the interactions of twelve children carrying out search tasks in a primary school…

A Database Approach to Content-based XML retrieval

NARCIS (Netherlands)

Hiemstra, Djoerd

2003-01-01

This paper describes a rst prototype system for content-based retrieval from XML data. The system's design supports both XPath queries and complex information retrieval queries based on a language modelling approach to information retrieval. Evaluation using the INEX benchmark shows that it is

Flexible Query Answering Systems 2006

DEFF Research Database (Denmark)

-computer interaction. The overall theme of the FQAS conferences is innovative query systems aimed at providing easy, flexible, and intuitive access to information. Such systems are intended to facilitate retrieval from information repositories such as databases, libraries, and the World-Wide Web. These repositories......This volume constitutes the proceedings of the Seventh International Conference on Flexible Query Answering Systems, FQAS 2006, held in Milan, Italy, on June 7--10, 2006. FQAS is the premier conference for researchers and practitioners concerned with the vital task of providing easy, flexible...... are typically equipped with standard query systems which are often inadequate, and the focus of FQAS is the development of query systems that are more expressive, informative, cooperative, and productive. These proceedings contain contributions from invited speakers and 53 original papers out of about 100...

Structuring Legacy Pathology Reports by openEHR Archetypes to Enable Semantic Querying.

Science.gov (United States)

Kropf, Stefan; Krücken, Peter; Mueller, Wolf; Denecke, Kerstin

2017-05-18

Clinical information is often stored as free text, e.g. in discharge summaries or pathology reports. These documents are semi-structured using section headers, numbered lists, items and classification strings. However, it is still challenging to retrieve relevant documents since keyword searches applied on complete unstructured documents result in many false positive retrieval results. We are concentrating on the processing of pathology reports as an example for unstructured clinical documents. The objective is to transform reports semi-automatically into an information structure that enables an improved access and retrieval of relevant data. The data is expected to be stored in a standardized, structured way to make it accessible for queries that are applied to specific sections of a document (section-sensitive queries) and for information reuse. Our processing pipeline comprises information modelling, section boundary detection and section-sensitive queries. For enabling a focused search in unstructured data, documents are automatically structured and transformed into a patient information model specified through openEHR archetypes. The resulting XML-based pathology electronic health records (PEHRs) are queried by XQuery and visualized by XSLT in HTML. Pathology reports (PRs) can be reliably structured into sections by a keyword-based approach. The information modelling using openEHR allows saving time in the modelling process since many archetypes can be reused. The resulting standardized, structured PEHRs allow accessing relevant data by retrieving data matching user queries. Mapping unstructured reports into a standardized information model is a practical solution for a better access to data. Archetype-based XML enables section-sensitive retrieval and visualisation by well-established XML techniques. Focussing the retrieval to particular sections has the potential of saving retrieval time and improving the accuracy of the retrieval.

Query Log Analysis of an Electronic Health Record Search Engine

Science.gov (United States)

Yang, Lei; Mei, Qiaozhu; Zheng, Kai; Hanauer, David A.

2011-01-01

We analyzed a longitudinal collection of query logs of a full-text search engine designed to facilitate information retrieval in electronic health records (EHR). The collection, 202,905 queries and 35,928 user sessions recorded over a course of 4 years, represents the information-seeking behavior of 533 medical professionals, including frontline practitioners, coding personnel, patient safety officers, and biomedical researchers for patient data stored in EHR systems. In this paper, we present descriptive statistics of the queries, a categorization of information needs manifested through the queries, as well as temporal patterns of the users’ information-seeking behavior. The results suggest that information needs in medical domain are substantially more sophisticated than those that general-purpose web search engines need to accommodate. Therefore, we envision there exists a significant challenge, along with significant opportunities, to provide intelligent query recommendations to facilitate information retrieval in EHR. PMID:22195150

Implementation of the common phrase index method on the phrase query for information retrieval

Science.gov (United States)

Fatmawati, Triyah; Zaman, Badrus; Werdiningsih, Indah

2017-08-01

As the development of technology, the process of finding information on the news text is easy, because the text of the news is not only distributed in print media, such as newspapers, but also in electronic media that can be accessed using the search engine. In the process of finding relevant documents on the search engine, a phrase often used as a query. The number of words that make up the phrase query and their position obviously affect the relevance of the document produced. As a result, the accuracy of the information obtained will be affected. Based on the outlined problem, the purpose of this research was to analyze the implementation of the common phrase index method on information retrieval. This research will be conducted in English news text and implemented on a prototype to determine the relevance level of the documents produced. The system is built with the stages of pre-processing, indexing, term weighting calculation, and cosine similarity calculation. Then the system will display the document search results in a sequence, based on the cosine similarity. Furthermore, system testing will be conducted using 100 documents and 20 queries. That result is then used for the evaluation stage. First, determine the relevant documents using kappa statistic calculation. Second, determine the system success rate using precision, recall, and F-measure calculation. In this research, the result of kappa statistic calculation was 0.71, so that the relevant documents are eligible for the system evaluation. Then the calculation of precision, recall, and F-measure produces precision of 0.37, recall of 0.50, and F-measure of 0.43. From this result can be said that the success rate of the system to produce relevant documents is low.

Evaluation of Sub Query Performance in SQL Server

Science.gov (United States)

Oktavia, Tanty; Sujarwo, Surya

2014-03-01

The paper explores several sub query methods used in a query and their impact on the query performance. The study uses experimental approach to evaluate the performance of each sub query methods combined with indexing strategy. The sub query methods consist of in, exists, relational operator and relational operator combined with top operator. The experimental shows that using relational operator combined with indexing strategy in sub query has greater performance compared with using same method without indexing strategy and also other methods. In summary, for application that emphasized on the performance of retrieving data from database, it better to use relational operator combined with indexing strategy. This study is done on Microsoft SQL Server 2012.

Fuzzy Querying: Issues and Perspectives..

Czech Academy of Sciences Publication Activity Database

Kacprzyk, J.; Pasi, G.; Vojtáš, Peter; Zadrozny, S.

2000-01-01

Roč. 36, č. 6 (2000), s. 605-616 ISSN 0023-5954 Institutional research plan: AV0Z1030915 Keywords : flexible querying * information retrieval * fuzzy databases Subject RIV: BA - General Mathematics http://dml.cz/handle/10338.dmlcz/135376

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.

Towards Intelligible Query Processing in Relevance Feedback-Based Image Retrieval Systems

OpenAIRE

Mohammed, Belkhatir

2008-01-01

We have specified within the scope of this paper a framework combining semantics and relational (spatial) characterizations within a coupled architecture in order to address the semantic gap. This framework is instantiated by an operational model based on a sound logic-based formalism, allowing to define a representation for image documents and a matching function to compare index and query structures. We have specified a query framework coupling keyword-based querying with a relevance feedba...

Secure image retrieval with multiple keys

Science.gov (United States)

Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang

2018-03-01

This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.

The Use of QBIC Content-Based Image Retrieval System

Directory of Open Access Journals (Sweden)

Ching-Yi Wu

2004-03-01

Full Text Available The fast increase in digital images has caught increasing attention on the development of image retrieval technologies. Content-based image retrieval (CBIR has become an important approach in retrieving image data from a large collection. This article reports our results on the use and users study of a CBIR system. Thirty-eight students majored in art and design were invited to use the IBM’s OBIC (Query by Image Content system through the Internet. Data from their information needs, behaviors, and retrieval strategies were collected through an in-depth interview, observation, and self-described think-aloud process. Important conclusions are:（1）There are four types of information needs for image data: implicit, inspirational, ever-changing, and purposive. The types of needs may change during the retrieval process. （2）CBIR is suitable for the example-type query, text retrieval is suitable for the scenario-type query, and image browsing is suitable for the symbolic query. （3）Different from text retrieval, detailed description of the query condition may lead to retrieval failure more easily. （4）CBIR is suitable for the domain-specific image collection, not for the images on the Word-Wide Web.[Article content in Chinese

Tag cloud generation for results of multiple keywords queries

DEFF Research Database (Denmark)

Leginus, Martin; Dolog, Peter; Lage, Ricardo Gomes

2013-01-01

In this paper we study tag cloud generation for retrieved results of multiple keyword queries. It is motivated by many real world scenarios such as personalization tasks, surveillance systems and information retrieval tasks defined with multiple keywords. We adjust the state-of-the-art tag cloud...... generation techniques for multiple keywords query results. Consequently, we conduct the extensive evaluation on top of three distinct collaborative tagging systems. The graph-based methods perform significantly better for the Movielens and Bibsonomy datasets. Tag cloud generation based on maximal coverage...

Web tools for effective retrieval, visualization, and evaluation of cardiology medical images and records

Science.gov (United States)

Masseroli, Marco; Pinciroli, Francesco

2000-12-01

To provide easy retrieval, integration and evaluation of multimodal cardiology images and data in a web browser environment, distributed application technologies and java programming were used to implement a client-server architecture based on software agents. The server side manages secure connections and queries to heterogeneous remote databases and file systems containing patient personal and clinical data. The client side is a Java applet running in a web browser and providing a friendly medical user interface to perform queries on patient and medical test dat and integrate and visualize properly the various query results. A set of tools based on Java Advanced Imaging API enables to process and analyze the retrieved cardiology images, and quantify their features in different regions of interest. The platform-independence Java technology makes the developed prototype easy to be managed in a centralized form and provided in each site where an intranet or internet connection can be located. Giving the healthcare providers effective tools for querying, visualizing and evaluating comprehensively cardiology medical images and records in all locations where they can need them- i.e. emergency, operating theaters, ward, or even outpatient clinics- the developed prototype represents an important aid in providing more efficient diagnoses and medical treatments.

Semantic querying of data guided by Formal Concept Analysis

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Napoli , Amedeo

2012-01-01

International audience; In this paper we present a novel approach to handle querying over a concept lattice of documents and annotations. We focus on the problem of "non-matching documents", which are those that, despite being semantically relevant to the user query, do not contain the query's elements and hence cannot be retrieved by typical string matching approaches. In order to find these documents, we modify the initial user query using the concept lattice as a guide. We achieve this by ...

Design Guidelines for a Content-Based Image Retrieval Color-Selection Interface

NARCIS (Netherlands)

Eggen, Berry; van den Broek, Egon; van der Veer, Gerrit C.; Kisters, Peter M.F.; Willems, Rob; Vuurpijl, Louis G.

2004-01-01

In Content-Based Image Retrieval (CBIR) two query-methods exist: query-by-example and query-by-memory. The user either selects an example image or selects image features retrieved from memory (such as color, texture, spatial attributes, and shape) to define his query. Hitherto, research on CBIR

Content-aware network storage system supporting metadata retrieval

Science.gov (United States)

Liu, Ke; Qin, Leihua; Zhou, Jingli; Nie, Xuejun

2008-12-01

Nowadays, content-based network storage has become the hot research spot of academy and corporation[1]. In order to solve the problem of hit rate decline causing by migration and achieve the content-based query, we exploit a new content-aware storage system which supports metadata retrieval to improve the query performance. Firstly, we extend the SCSI command descriptor block to enable system understand those self-defined query requests. Secondly, the extracted metadata is encoded by extensible markup language to improve the universality. Thirdly, according to the demand of information lifecycle management (ILM), we store those data in different storage level and use corresponding query strategy to retrieval them. Fourthly, as the file content identifier plays an important role in locating data and calculating block correlation, we use it to fetch files and sort query results through friendly user interface. Finally, the experiments indicate that the retrieval strategy and sort algorithm have enhanced the retrieval efficiency and precision.

Natural language query system design for interactive information storage and retrieval systems. Presentation visuals. M.S. Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

Science.gov (United States)

Dominick, Wayne D. (Editor); Liu, I-Hsiung

1985-01-01

This Working Paper Series entry represents a collection of presentation visuals associated with the companion report entitled Natural Language Query System Design for Interactive Information Storage and Retrieval Systems, USL/DBMS NASA/RECON Working Paper Series report number DBMS.NASA/RECON-17.

Robust segmentation and retrieval of environmental sounds

Science.gov (United States)

Wichern, Gordon

The proliferation of mobile computing has provided much of the world with the ability to record any sound of interest, or possibly every sound heard in a lifetime. The technology to continuously record the auditory world has applications in surveillance, biological monitoring of non-human animal sounds, and urban planning. Unfortunately, the ability to record anything has led to an audio data deluge, where there are more recordings than time to listen. Thus, access to these archives depends on efficient techniques for segmentation (determining where sound events begin and end), indexing (storing sufficient information with each event to distinguish it from other events), and retrieval (searching for and finding desired events). While many such techniques have been developed for speech and music sounds, the environmental and natural sounds that compose the majority of our aural world are often overlooked. The process of analyzing audio signals typically begins with the process of acoustic feature extraction where a frame of raw audio (e.g., 50 milliseconds) is converted into a feature vector summarizing the audio content. In this dissertation, a dynamic Bayesian network (DBN) is used to monitor changes in acoustic features in order to determine the segmentation of continuously recorded audio signals. Experiments demonstrate effective segmentation performance on test sets of environmental sounds recorded in both indoor and outdoor environments. Once segmented, every sound event is indexed with a probabilistic model, summarizing the evolution of acoustic features over the course of the event. Indexed sound events are then retrieved from the database using different query modalities. Two important query types are sound queries (query-by-example) and semantic queries (query-by-text). By treating each sound event and semantic concept in the database as a node in an undirected graph, a hybrid (content/semantic) network structure is developed. This hybrid network can

Group-by Skyline Query Processing in Relational Engines

DEFF Research Database (Denmark)

Yiu, Man Lung; Luk, Ming-Hay; Lo, Eric

2009-01-01

the missing cost model for the BBS algorithm. Experimental results show that our techniques are able to devise the best query plans for a variety of group-by skyline queries. Our focus is on algorithms that can be directly implemented in today's commercial database systems without the addition of new access......The skyline operator was first proposed in 2001 for retrieving interesting tuples from a dataset. Since then, 100+ skyline-related papers have been published; however, we discovered that one of the most intuitive and practical type of skyline queries, namely, group-by skyline queries remains...

Designing and Implementing a Cross-Language Information Retrieval System Using Linguistic Corpora

Directory of Open Access Journals (Sweden)

Amin Nezarat

2012-03-01

Full Text Available Information retrieval (IR is a crucial area of natural language processing (NLP and can be defined as finding documents whose content is relevant to the query need of a user. Cross-language information retrieval (CLIR refers to a kind of information retrieval in which the language of the query and that of searched document are different. In fact, it is a retrieval process where the user presents queries in one language to retrieve documents in another language. This paper tried to construct a bilingual lexicon of parallel chunks of English and Persian from two very large monolingual corpora an English-Persian parallel corpus which could be directly applied to cross-language information retrieval tasks. For this purpose, a statistical measure known as Association Score (AS was used to compute the association value between every two corresponding chunks in the corpus using a couple of complicated algorithms. Once the CLIR system was developed using this bilingual lexicon, an experiment was performed on a set of one hundred English and Persian phrases and collocations to see to what extend this system was effective in assisting the users find the most relevant and suitable equivalents of their queries in either language.

A Query System Implementation Case Study.

Science.gov (United States)

Hiser, Judith N.; Neil, M. Elizabeth

1985-01-01

The Department of Administrative Programming Services of Clemson University investigated products available in user-friendly retrieval systems. The test of INTELLECT, a natural language query system written by Artifical Intelligence Corporation, is described. (Author/MLW)

Secure Nearest Neighbor Query on Crowd-Sensing Data

Directory of Open Access Journals (Sweden)

Ke Cheng

2016-09-01

Full Text Available Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes.

Rhetorical relations for information retrieval

DEFF Research Database (Denmark)

Lioma, Christina; Larsen, Birger; Lu, Wei

2012-01-01

-called discourse structure has been applied successfully to several natural language processing tasks. This work studies the use of rhetorical relations for Information Retrieval (IR): Is there a correlation between certain rhetorical relations and retrieval performance? Can knowledge about a document’s rhetorical...... relations be useful to IR? We present a language model modification that considers rhetorical relations when estimating the relevance of a document to a query. Empirical evaluation of different versions of our model on TREC settings shows that certain rhetorical relations can benefit retrieval effectiveness...

BioFed: federated query processing over life sciences linked open data.

Science.gov (United States)

Hasnain, Ali; Mehmood, Qaiser; Sana E Zainab, Syeda; Saleem, Muhammad; Warren, Claude; Zehra, Durre; Decker, Stefan; Rebholz-Schuhmann, Dietrich

2017-03-15

Biomedical data, e.g. from knowledge bases and ontologies, is increasingly made available following open linked data principles, at best as RDF triple data. This is a necessary step towards unified access to biological data sets, but this still requires solutions to query multiple endpoints for their heterogeneous data to eventually retrieve all the meaningful information. Suggested solutions are based on query federation approaches, which require the submission of SPARQL queries to endpoints. Due to the size and complexity of available data, these solutions have to be optimised for efficient retrieval times and for users in life sciences research. Last but not least, over time, the reliability of data resources in terms of access and quality have to be monitored. Our solution (BioFed) federates data over 130 SPARQL endpoints in life sciences and tailors query submission according to the provenance information. BioFed has been evaluated against the state of the art solution FedX and forms an important benchmark for the life science domain. The efficient cataloguing approach of the federated query processing system 'BioFed', the triple pattern wise source selection and the semantic source normalisation forms the core to our solution. It gathers and integrates data from newly identified public endpoints for federated access. Basic provenance information is linked to the retrieved data. Last but not least, BioFed makes use of the latest SPARQL standard (i.e., 1.1) to leverage the full benefits for query federation. The evaluation is based on 10 simple and 10 complex queries, which address data in 10 major and very popular data sources (e.g., Dugbank, Sider). BioFed is a solution for a single-point-of-access for a large number of SPARQL endpoints providing life science data. It facilitates efficient query generation for data access and provides basic provenance information in combination with the retrieved data. BioFed fully supports SPARQL 1.1 and gives access to the

SPARQL Query Re-writing Using Partonomy Based Transformation Rules

Science.gov (United States)

Jain, Prateek; Yeh, Peter Z.; Verma, Kunal; Henson, Cory A.; Sheth, Amit P.

Often the information present in a spatial knowledge base is represented at a different level of granularity and abstraction than the query constraints. For querying ontology's containing spatial information, the precise relationships between spatial entities has to be specified in the basic graph pattern of SPARQL query which can result in long and complex queries. We present a novel approach to help users intuitively write SPARQL queries to query spatial data, rather than relying on knowledge of the ontology structure. Our framework re-writes queries, using transformation rules to exploit part-whole relations between geographical entities to address the mismatches between query constraints and knowledge base. Our experiments were performed on completely third party datasets and queries. Evaluations were performed on Geonames dataset using questions from National Geographic Bee serialized into SPARQL and British Administrative Geography Ontology using questions from a popular trivia website. These experiments demonstrate high precision in retrieval of results and ease in writing queries.

Towards Verbalizing SPARQL Queries in Arabic

Directory of Open Access Journals (Sweden)

I. Al Agha

2016-04-01

Full Text Available With the wide spread of Open Linked Data and Semantic Web technologies, a larger amount of data has been published on the Web in the RDF and OWL formats. This data can be queried using SPARQL, the Semantic Web Query Language. SPARQL cannot be understood by ordinary users and is not directly accessible to humans, and thus they will not be able to check whether the retrieved answers truly correspond to the intended information need. Driven by this challenge, natural language generation from SPARQL data has recently attracted a considerable attention. However, most existing solutions to verbalize SPARQL in natural language focused on English and Latin-based languages. Little effort has been made on the Arabic language which has different characteristics and morphology. This work aims to particularly help Arab users to perceive SPARQL queries on the Semantic Web by translating SPARQL to Arabic. It proposes an approach that gets a SPARQL query as an input and generates a query expressed in Arabic as an output. The translation process combines both morpho-syntactic analysis and language dependencies to generate a legible and understandable Arabic query. The approach was preliminary assessed with a sample query set, and results indicated that 75% of the queries were correctly translated into Arabic.

Toward privacy-preserving JPEG image retrieval

Science.gov (United States)

Cheng, Hang; Wang, Jingyue; Wang, Meiqing; Zhong, Shangping

2017-07-01

This paper proposes a privacy-preserving retrieval scheme for JPEG images based on local variance. Three parties are involved in the scheme: the content owner, the server, and the authorized user. The content owner encrypts JPEG images for privacy protection by jointly using permutation cipher and stream cipher, and then, the encrypted versions are uploaded to the server. With an encrypted query image provided by an authorized user, the server may extract blockwise local variances in different directions without knowing the plaintext content. After that, it can calculate the similarity between the encrypted query image and each encrypted database image by a local variance-based feature comparison mechanism. The authorized user with the encryption key can decrypt the returned encrypted images with plaintext content similar to the query image. The experimental results show that the proposed scheme not only provides effective privacy-preserving retrieval service but also ensures both format compliance and file size preservation for encrypted JPEG images.

Bioqueries: a collaborative environment to create, explore and share SPARQL queries in Life Sciences

OpenAIRE

García-Godoy, Maria Jesús; López-Camacho, Esteban; Navas-Delgado, Ismael; Aldana-Montes, Jose Francisco

2016-01-01

Bioqueries provides a collaborative environment to create, explore, execute, clone and share SPARQL queries (including Federated Queries). Federated SPARQL queries can retrieve information from more than one data source. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.

W-transform method for feature-oriented multiresolution image retrieval

Energy Technology Data Exchange (ETDEWEB)

Kwong, M.K.; Lin, B. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

1995-07-01

Image database management is important in the development of multimedia technology. Since an enormous amount of digital images is likely to be generated within the next few decades in order to integrate computers, television, VCR, cables, telephone and various imaging devices. Effective image indexing and retrieval systems are urgently needed so that images can be easily organized, searched, transmitted, and presented. Here, the authors present a local-feature-oriented image indexing and retrieval method based on Kwong, and Tang`s W-transform. Multiresolution histogram comparison is an effective method for content-based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W-transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In this approach, the histograms of the local features of images are used in the indexing, system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

Lost in translation? A multilingual Query Builder improves the quality of PubMed queries: a randomised controlled trial.

Science.gov (United States)

Schuers, Matthieu; Joulakian, Mher; Kerdelhué, Gaetan; Segas, Léa; Grosjean, Julien; Darmoni, Stéfan J; Griffon, Nicolas

2017-07-03

MEDLINE is the most widely used medical bibliographic database in the world. Most of its citations are in English and this can be an obstacle for some researchers to access the information the database contains. We created a multilingual query builder to facilitate access to the PubMed subset using a language other than English. The aim of our study was to assess the impact of this multilingual query builder on the quality of PubMed queries for non-native English speaking physicians and medical researchers. A randomised controlled study was conducted among French speaking general practice residents. We designed a multi-lingual query builder to facilitate information retrieval, based on available MeSH translations and providing users with both an interface and a controlled vocabulary in their own language. Participating residents were randomly allocated either the French or the English version of the query builder. They were asked to translate 12 short medical questions into MeSH queries. The main outcome was the quality of the query. Two librarians blind to the arm independently evaluated each query, using a modified published classification that differentiated eight types of errors. Twenty residents used the French version of the query builder and 22 used the English version. 492 queries were analysed. There were significantly more perfect queries in the French group vs. the English group (respectively 37.9% vs. 17.9%; p PubMed queries in particular for researchers whose first language is not English.

IMAGE DESCRIPTIONS FOR SKETCH BASED IMAGE RETRIEVAL

OpenAIRE

SAAVEDRA RONDO, JOSE MANUEL; SAAVEDRA RONDO, JOSE MANUEL

2008-01-01

Due to the massive use of Internet together with the proliferation of media devices, content based image retrieval has become an active discipline in computer science. A common content based image retrieval approach requires that the user gives a regular image (e.g, a photo) as a query. However, having a regular image as query may be a serious problem. Indeed, people commonly use an image retrieval system because they do not count on the desired image. An easy alternative way t...

Semantic concept-enriched dependence model for medical information retrieval.

Science.gov (United States)

Choi, Sungbin; Choi, Jinwook; Yoo, Sooyoung; Kim, Heechun; Lee, Youngho

2014-02-01

In medical information retrieval research, semantic resources have been mostly used by expanding the original query terms or estimating the concept importance weight. However, implicit term-dependency information contained in semantic concept terms has been overlooked or at least underused in most previous studies. In this study, we incorporate a semantic concept-based term-dependence feature into a formal retrieval model to improve its ranking performance. Standardized medical concept terms used by medical professionals were assumed to have implicit dependency within the same concept. We hypothesized that, by elaborately revising the ranking algorithms to favor documents that preserve those implicit dependencies, the ranking performance could be improved. The implicit dependence features are harvested from the original query using MetaMap. These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM). We designed four different variants of the model, with each variant having distinct characteristics in the feature formulation method. We performed leave-one-out cross validations on both a clinical document corpus (TREC Medical records track) and a medical literature corpus (OHSUMED), which are representative test collections in medical information retrieval research. Our semantic concept-enriched dependence model consistently outperformed other state-of-the-art retrieval methods. Analysis shows that the performance gain has occurred independently of the concept's explicit importance in the query. By capturing implicit knowledge with regard to the query term relationships and incorporating them into a ranking model, we could build a more robust and effective retrieval model, independent of the concept importance. Copyright © 2013 Elsevier Inc. All rights reserved.

Ad-hoc Content-based Queries and Data Analysis for Virtual Observatories, Phase II

Data.gov (United States)

National Aeronautics and Space Administration — Aquilent, Inc. proposes to support ad-hoc, content-based query and data retrieval from virtual observatories (VxO) by developing 1) Higher Order Query Services that...

Evolutionary Algorithms for Boolean Queries Optimization

Czech Academy of Sciences Publication Activity Database

Húsek, Dušan; Snášel, Václav; Neruda, Roman; Owais, S.S.J.; Krömer, P.

2006-01-01

Roč. 3, č. 1 (2006), s. 15-20 ISSN 1790-0832 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * information retrieval * Boolean query Subject RIV: BA - General Mathematics

Automated Medical Literature Retrieval

Directory of Open Access Journals (Sweden)

David Hawking

2012-09-01

Full Text Available Background The constantly growing publication rate of medical research articles puts increasing pressure on medical specialists who need to be aware of the recent developments in their field. The currently used literature retrieval systems allow researchers to find specific papers; however the search task is still repetitive and time-consuming. Aims In this paper we describe a system that retrieves medical publications by automatically generating queries based on data from an electronic patient record. This allows the doctor to focus on medical issues and provide an improved service to the patient, with higher confidence that it is underpinned by current research. Method Our research prototype automatically generates query terms based on the patient record and adds weight factors for each term. Currently the patient’s age is taken into account with a fuzzy logic derived weight, and terms describing blood-related anomalies are derived from recent blood test results. Conditionally selected homonyms are used for query expansion. The query retrieves matching records from a local index of PubMed publications and displays results in descending relevance for the given patient. Recent publications are clearly highlighted for instant recognition by the researcher. Results Nine medical specialists from the Royal Adelaide Hospital evaluated the system and submitted pre-trial and post-trial questionnaires. Throughout the study we received positive feedback as doctors felt the support provided by the prototype was useful, and which they would like to use in their daily routine. Conclusion By supporting the time-consuming task of query formulation and iterative modification as well as by presenting the search results in order of relevance for the specific patient, literature retrieval becomes part of the daily workflow of busy professionals.

a Novel Approach of Indexing and Retrieving Spatial Polygons for Efficient Spatial Region Queries

Science.gov (United States)

Zhao, J. H.; Wang, X. Z.; Wang, F. Y.; Shen, Z. H.; Zhou, Y. C.; Wang, Y. L.

2017-10-01

Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree) suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.

A NOVEL APPROACH OF INDEXING AND RETRIEVING SPATIAL POLYGONS FOR EFFICIENT SPATIAL REGION QUERIES

Directory of Open Access Journals (Sweden)

J. H. Zhao

2017-10-01

Full Text Available Spatial region queries are more and more widely used in web-based applications. Mechanisms to provide efficient query processing over geospatial data are essential. However, due to the massive geospatial data volume, heavy geometric computation, and high access concurrency, it is difficult to get response in real time. Spatial indexes are usually used in this situation. In this paper, based on k-d tree, we introduce a distributed KD-Tree (DKD-Tree suitbable for polygon data, and a two-step query algorithm. The spatial index construction is recursive and iterative, and the query is an in memory process. Both the index and query methods can be processed in parallel, and are implemented based on HDFS, Spark and Redis. Experiments on a large volume of Remote Sensing images metadata have been carried out, and the advantages of our method are investigated by comparing with spatial region queries executed on PostgreSQL and PostGIS. Results show that our approach not only greatly improves the efficiency of spatial region query, but also has good scalability, Moreover, the two-step spatial range query algorithm can also save cluster resources to support a large number of concurrent queries. Therefore, this method is very useful when building large geographic information systems.

Integrating user profile in medical CBIR systems to answer perceptual similarity queries

Science.gov (United States)

Bugatti, Pedro H.; Kaster, Daniel S.; Ponciano-Silva, Marcelo; Traina, Agma J. M.; Traina, Caetano, Jr.

2011-03-01

Techniques for Content-Based Image Retrieval (CBIR) have been intensively explored due to the increase in the amount of captured images and the need of fast retrieval of them. The medical field is a specific example that generates a large flow of information, especially digital images employed for diagnosing. One issue that still remains unsolved deals with how to reach the perceptual similarity. That is, to achieve an effective retrieval, one must characterize and quantify the perceptual similarity regarding the specialist in the field. Therefore, the present paper was conceived to fill in this gap creating a consistent support to perform similarity queries over medical images, maintaining the semantics of a given query desired by the user. CBIR systems relying in relevance feedback techniques usually request the users to label relevant images. In this paper, we present a simple but highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The user profiles maintain the settings desired for each user, allowing tuning the similarity assessment, which encompasses dynamically changing the distance function employed through an interactive process. Experiments using computed tomography lung images show that the proposed approach is effective in capturing the users' perception.

An Evaluation of the Interactive Query Expansion in an Online Library Catalogue with a Graphical User Interface.

Science.gov (United States)

Hancock-Beaulieu, Micheline; And Others

1995-01-01

An online library catalog was used to evaluate an interactive query expansion facility based on relevance feedback for the Okapi, probabilistic, term weighting, retrieval system. A graphical user interface allowed searchers to select candidate terms extracted from relevant retrieved items to reformulate queries. Results suggested that the…

Fast Inbound Top-K Query for Random Walk with Restart.

Science.gov (United States)

Zhang, Chao; Jiang, Shan; Chen, Yucheng; Sun, Yidan; Han, Jiawei

2015-09-01

Random walk with restart (RWR) is widely recognized as one of the most important node proximity measures for graphs, as it captures the holistic graph structure and is robust to noise in the graph. In this paper, we study a novel query based on the RWR measure, called the inbound top-k (Ink) query. Given a query node q and a number k , the Ink query aims at retrieving k nodes in the graph that have the largest weighted RWR scores to q . Ink queries can be highly useful for various applications such as traffic scheduling, disease treatment, and targeted advertising. Nevertheless, none of the existing RWR computation techniques can accurately and efficiently process the Ink query in large graphs. We propose two algorithms, namely Squeeze and Ripple, both of which can accurately answer the Ink query in a fast and incremental manner. To identify the top- k nodes, Squeeze iteratively performs matrix-vector multiplication and estimates the lower and upper bounds for all the nodes in the graph. Ripple employs a more aggressive strategy by only estimating the RWR scores for the nodes falling in the vicinity of q , the nodes outside the vicinity do not need to be evaluated because their RWR scores are propagated from the boundary of the vicinity and thus upper bounded. Ripple incrementally expands the vicinity until the top- k result set can be obtained. Our extensive experiments on real-life graph data sets show that Ink queries can retrieve interesting results, and the proposed algorithms are orders of magnitude faster than state-of-the-art method.

Boolean Queries Optimization by Genetic Algorithms

Czech Academy of Sciences Publication Activity Database

Húsek, Dušan; Owais, S.S.J.; Krömer, P.; Snášel, Václav

2005-01-01

Roč. 15, - (2005), s. 395-409 ISSN 1210-0552 R&D Projects: GA AV ČR 1ET100300414 Institutional research plan: CEZ:AV0Z10300504 Keywords : evolutionary algorithms * genetic algorithms * genetic programming * information retrieval * Boolean query Subject RIV: BB - Applied Statistics, Operational Research

Query Optimizations over Decentralized RDF Graphs

KAUST Repository

Abdelaziz, Ibrahim

2017-05-18

Applications in life sciences, decentralized social networks, Internet of Things, and statistical linked dataspaces integrate data from multiple decentralized RDF graphs via SPARQL queries. Several approaches have been proposed to optimize query processing over a small number of heterogeneous data sources by utilizing schema information. In the case of schema similarity and interlinks among sources, these approaches cause unnecessary data retrieval and communication, leading to poor scalability and response time. This paper addresses these limitations and presents Lusail, a system for scalable and efficient SPARQL query processing over decentralized graphs. Lusail achieves scalability and low query response time through various optimizations at compile and run times. At compile time, we use a novel locality-aware query decomposition technique that maximizes the number of query triple patterns sent together to a source based on the actual location of the instances satisfying these triple patterns. At run time, we use selectivity-awareness and parallel query execution to reduce network latency and to increase parallelism by delaying the execution of subqueries expected to return large results. We evaluate Lusail using real and synthetic benchmarks, with data sizes up to billions of triples on an in-house cluster and a public cloud. We show that Lusail outperforms state-of-the-art systems by orders of magnitude in terms of scalability and response time.

Experiments with a novel content-based image retrieval software: can we eliminate classification systems in adolescent idiopathic scoliosis?

Science.gov (United States)

Menon, K Venugopal; Kumar, Dinesh; Thomas, Tessamma

2014-02-01

Study Design Preliminary evaluation of new tool. Objective To ascertain whether the newly developed content-based image retrieval (CBIR) software can be used successfully to retrieve images of similar cases of adolescent idiopathic scoliosis (AIS) from a database to help plan treatment without adhering to a classification scheme. Methods Sixty-two operated cases of AIS were entered into the newly developed CBIR database. Five new cases of different curve patterns were used as query images. The images were fed into the CBIR database that retrieved similar images from the existing cases. These were analyzed by a senior surgeon for conformity to the query image. Results Within the limits of variability set for the query system, all the resultant images conformed to the query image. One case had no similar match in the series. The other four retrieved several images that were matching with the query. No matching case was left out in the series. The postoperative images were then analyzed to check for surgical strategies. Broad guidelines for treatment could be derived from the results. More precise query settings, inclusion of bending films, and a larger database will enhance accurate retrieval and better decision making. Conclusion The CBIR system is an effective tool for accurate documentation and retrieval of scoliosis images. Broad guidelines for surgical strategies can be made from the postoperative images of the existing cases without adhering to any classification scheme.

A Survey: Framework of an Information Retrieval for Malay Translated Hadith Document

Directory of Open Access Journals (Sweden)

Zulkefli Nurul Syeilla Syazhween

2017-01-01

Full Text Available This paper reviews and analyses the limitation of the existing method used in the IR process in retrieving Malay Translated Hadith documents related to the search request. Traditional Malay Translated Hadith retrieval system has not focused on semantic extraction from text. The bag-of-words representation ignores the conceptual similarity of information in the query text and documents, which produce unsatisfactory retrieval results. Therefore, a more efficient IR framework is needed. This paper claims that the significant information extraction and subject-related information are actually important because the clues from this information can be used to search and find the relevance document to a query. Also, unimportant information can be discarded to represent the document content. So, semantic understanding of query and document is necessary to improve the effectiveness and accuracy of retrieval results for this domain study. Therefore, advance research is needed and it will be experimented in the future work. It is hoped that it will help users to search and find information regarding to the Malay Translated Hadith document.

External query expansion in the blogosphere

NARCIS (Netherlands)

Weerkamp, W.; de Rijke, M.; Voorhees, E.M.; Buckland, L.P.

2009-01-01

We describe the participation of the University of Amsterdam’s ILPS group in the blog track at TREC 2008. We mainly explored different ways of using external corpora to expand the original query. In the blog post retrieval task we did not succeed in improving over a simple baseline (equal weights

Evaluating Trajectory Queries over Imprecise Location Data

DEFF Research Database (Denmark)

Xie, Scott, Xike; Cheng, Reynold; Yiu, Man Lung

2012-01-01

Trajectory queries, which retrieve nearby objects for every point of a given route, can be used to identify alerts of potential threats along a vessel route, or monitor the adjacent rescuers to a travel path. However, the locations of these objects (e.g., threats, succours) may not be precisely...... obtained due to hardware limitations of measuring devices, as well as the constantly-changing nature of the external environment. Ignoring data uncertainty can render low query quality, and cause undesirable consequences such as missing alerts of threats and poor response time in rescue operations. Also......, the query is quite time-consuming, since all the points on the trajectory are considered. In this paper, we study how to efficiently evaluate trajectory queries over imprecise location data, by proposing a new concept called the u-bisector. In general, the u-bisector is an extension of bisector to handle...

Document image retrieval through word shape coding.

Science.gov (United States)

Lu, Shijian; Li, Linlin; Tan, Chew Lim

2008-11-01

This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.

An Efficient Algorithm for Maximizing Range Sum Queries in a Road Network

Directory of Open Access Journals (Sweden)

Tien-Khoi Phan

2014-01-01

Full Text Available Given a set of positive-weighted points and a query rectangle r (specified by a client of given extents, the goal of a maximizing range sum (MaxRS query is to find the optimal location of r such that the total weights of all the points covered by r are maximized. All existing methods for processing MaxRS queries assume the Euclidean distance metric. In many location-based applications, however, the motion of a client may be constrained by an underlying (spatial road network; that is, the client cannot move freely in space. This paper addresses the problem of processing MaxRS queries in a road network. We propose the external-memory algorithm that is suited for a large road network database. In addition, in contrast to the existing methods, which retrieve only one optimal location, our proposed algorithm retrieves all the possible optimal locations. Through simulations, we evaluate the performance of the proposed algorithm.

Human motion retrieval from hand-drawn sketch.

Science.gov (United States)

Chao, Min-Wen; Lin, Chao-Hung; Assa, Jackie; Lee, Tong-Yee

2012-05-01

The rapid growth of motion capture data increases the importance of motion retrieval. The majority of the existing motion retrieval approaches are based on a labor-intensive step in which the user browses and selects a desired query motion clip from the large motion clip database. In this work, a novel sketching interface for defining the query is presented. This simple approach allows users to define the required motion by sketching several motion strokes over a drawn character, which requires less effort and extends the users’ expressiveness. To support the real-time interface, a specialized encoding of the motions and the hand-drawn query is required. Here, we introduce a novel hierarchical encoding scheme based on a set of orthonormal spherical harmonic (SH) basis functions, which provides a compact representation, and avoids the CPU/processing intensive stage of temporal alignment used by previous solutions. Experimental results show that the proposed approach can well retrieve the motions, and is capable of retrieve logically and numerically similar motions, which is superior to previous approaches. The user study shows that the proposed system can be a useful tool to input motion query if the users are familiar with it. Finally, an application of generating a 3D animation from a hand-drawn comics strip is demonstrated.

Matching health information seekers' queries to medical terms.

Science.gov (United States)

Soualmia, Lina F; Prieur-Gaston, Elise; Moalla, Zied; Lecroq, Thierry; Darmoni, Stéfan J

2012-01-01

The Internet is a major source of health information but most seekers are not familiar with medical vocabularies. Hence, their searches fail due to bad query formulation. Several methods have been proposed to improve information retrieval: query expansion, syntactic and semantic techniques or knowledge-based methods. However, it would be useful to clean those queries which are misspelled. In this paper, we propose a simple yet efficient method in order to correct misspellings of queries submitted by health information seekers to a medical online search tool. In addition to query normalizations and exact phonetic term matching, we tested two approximate string comparators: the similarity score function of Stoilos and the normalized Levenshtein edit distance. We propose here to combine them to increase the number of matched medical terms in French. We first took a sample of query logs to determine the thresholds and processing times. In the second run, at a greater scale we tested different combinations of query normalizations before or after misspelling correction with the retained thresholds in the first run. According to the total number of suggestions (around 163, the number of the first sample of queries), at a threshold comparator score of 0.3, the normalized Levenshtein edit distance gave the highest F-Measure (88.15%) and at a threshold comparator score of 0.7, the Stoilos function gave the highest F-Measure (84.31%). By combining Levenshtein and Stoilos, the highest F-Measure (80.28%) is obtained with 0.2 and 0.7 thresholds respectively. However, queries are composed by several terms that may be combination of medical terms. The process of query normalization and segmentation is thus required. The highest F-Measure (64.18%) is obtained when this process is realized before spelling-correction. Despite the widely known high performance of the normalized edit distance of Levenshtein, we show in this paper that its combination with the Stoilos algorithm improved

Information Retrieval on social network: An Adaptive Proof

Science.gov (United States)

Elveny, M.; Syah, R.; Elfida, M.; Nasution, M. K. M.

2018-01-01

Information Retrieval has become one of the areas for studying to get the trusty information, with which the recall and precision become the measurement form that represents it. Nevertheless, development in certain scientific fields make it possible to improve the performance of the Information Retrieval. In this case, through social networks whereby the role of social actor degrees plays a role. This is an implication of the query in which co-occurrence becomes an indication of social networks. An adaptive approach we use by involving this query in sequence to a stand-alone query, it has proven the relationship among them.

Intelligent Information Retrieval: An Introduction.

Science.gov (United States)

Gauch, Susan

1992-01-01

Discusses the application of artificial intelligence to online information retrieval systems and describes several systems: (1) CANSEARCH, from MEDLINE; (2) Intelligent Interface for Information Retrieval (I3R); (3) Gausch's Query Reformulation; (4) Environmental Pollution Expert (EP-X); (5) PLEXUS (gardening); and (6) SCISOR (corporate…

User centered and ontology based information retrieval system for life sciences.

Science.gov (United States)

Sy, Mohameth-François; Ranwez, Sylvie; Montmain, Jacky; Regnault, Armelle; Crampes, Michel; Ranwez, Vincent

2012-01-25

Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. The ontology based information retrieval system described in this paper (OBIRS) is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens relevant information to provide decision help.

User centered and ontology based information retrieval system for life sciences

Directory of Open Access Journals (Sweden)

Sy Mohameth-François

2012-01-01

Full Text Available Abstract Background Because of the increasing number of electronic resources, designing efficient tools to retrieve and exploit them is a major challenge. Some improvements have been offered by semantic Web technologies and applications based on domain ontologies. In life science, for instance, the Gene Ontology is widely exploited in genomic applications and the Medical Subject Headings is the basis of biomedical publications indexation and information retrieval process proposed by PubMed. However current search engines suffer from two main drawbacks: there is limited user interaction with the list of retrieved resources and no explanation for their adequacy to the query is provided. Users may thus be confused by the selection and have no idea on how to adapt their queries so that the results match their expectations. Results This paper describes an information retrieval system that relies on domain ontology to widen the set of relevant documents that is retrieved and that uses a graphical rendering of query results to favor user interactions. Semantic proximities between ontology concepts and aggregating models are used to assess documents adequacy with respect to a query. The selection of documents is displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user's query; this man/machine interface favors a more interactive and iterative exploration of data corpus, by facilitating query concepts weighting and visual explanation. We illustrate the benefit of using this information retrieval system on two case studies one of which aiming at collecting human genes related to transcription factors involved in hemopoiesis pathway. Conclusions The ontology based information retrieval system described in this paper (OBIRS is freely available at: http://www.ontotoolkit.mines-ales.fr/ObirsClient/. This environment is a first step towards a user centred application in which the system enlightens

Conceptual querying through ontologies

DEFF Research Database (Denmark)

Andreasen, Troels; Bulskov, Henrik

2009-01-01

is motivated by an obvious need for users to survey huge volumes of objects in query answers. An ontology formalism and a special notion of-instantiated ontology" are introduced. The latter is a structure reflecting the content in the document collection in that; it is a restriction of a general world......We present here ail approach to conceptual querying where the aim is, given a collection of textual database objects or documents, to target an abstraction of the entire database content in terms of the concepts appearing in documents, rather than the documents in the collection. The approach...... knowledge ontology to the concepts instantiated in the collection. The notion of ontology-based similarity is briefly described, language constructs for direct navigation and retrieval of concepts in the ontology are discussed and approaches to conceptual summarization are presented....

Analysis of queries sent to PubMed at the point of care: observation of search behaviour in a medical teaching hospital.

NARCIS (Netherlands)

Hoogendam, A.; Stalenhoef, A.F.H.; Vries Robbe, P.F. de; Overbeke, A.J.P.M.

2008-01-01

BACKGROUND: The use of PubMed to answer daily medical care questions is limited because it is challenging to retrieve a small set of relevant articles and time is restricted. Knowing what aspects of queries are likely to retrieve relevant articles can increase the effectiveness of PubMed searches.

Query-by-example surgical activity detection.

Science.gov (United States)

Gao, Yixin; Vedula, S Swaroop; Lee, Gyusung I; Lee, Mija R; Khudanpur, Sanjeev; Hager, Gregory D

2016-06-01

Easy acquisition of surgical data opens many opportunities to automate skill evaluation and teaching. Current technology to search tool motion data for surgical activity segments of interest is limited by the need for manual pre-processing, which can be prohibitive at scale. We developed a content-based information retrieval method, query-by-example (QBE), to automatically detect activity segments within surgical data recordings of long duration that match a query. The example segment of interest (query) and the surgical data recording (target trial) are time series of kinematics. Our approach includes an unsupervised feature learning module using a stacked denoising autoencoder (SDAE), two scoring modules based on asymmetric subsequence dynamic time warping (AS-DTW) and template matching, respectively, and a detection module. A distance matrix of the query against the trial is computed using the SDAE features, followed by AS-DTW combined with template scoring, to generate a ranked list of candidate subsequences (substrings). To evaluate the quality of the ranked list against the ground-truth, thresholding conventional DTW distances and bipartite matching are applied. We computed the recall, precision, F1-score, and a Jaccard index-based score on three experimental setups. We evaluated our QBE method using a suture throw maneuver as the query, on two tool motion datasets (JIGSAWS and MISTIC-SL) captured in a training laboratory. We observed a recall of 93, 90 and 87 % and a precision of 93, 91, and 88 % with same surgeon same trial (SSST), same surgeon different trial (SSDT) and different surgeon (DS) experiment setups on JIGSAWS, and a recall of 87, 81 and 75 % and a precision of 72, 61, and 53 % with SSST, SSDT and DS experiment setups on MISTIC-SL, respectively. We developed a novel, content-based information retrieval method to automatically detect multiple instances of an activity within long surgical recordings. Our method demonstrated adequate recall

IQARIS : a tool for the intelligent querying, analysis, and retrieval from information systems

International Nuclear Information System (INIS)

Hummel, J. R.; Silver, R. B.

2002-01-01

Information glut is one of the primary characteristics of the electronic age. Managing such large volumes of information (e.g., keeping track of the types, where they are, their relationships, who controls them, etc.) can be done efficiently with an intelligent, user-oriented information management system. The purpose of this paper is to describe a concept for managing information resources based on an intelligent information technology system developed by the Argonne National Laboratory for managing digital libraries. The Argonne system, Intelligent Query (IQ), enables users to query digital libraries and view the holdings that match the query from different perspectives

Utah Text Retrieval Project

Energy Technology Data Exchange (ETDEWEB)

Hollaar, L A

1983-10-01

The Utah Text Retrieval project seeks well-engineered solutions to the implementation of large, inexpensive, rapid text information retrieval systems. The project has three major components. Perhaps the best known is the work on the specialized processors, particularly search engines, necessary to achieve the desired performance and cost. The other two concern the user interface to the system and the system's internal structure. The work on user interface development is not only concentrating on the syntax and semantics of the query language, but also on the overall environment the system presents to the user. Environmental enhancements include convenient ways to browse through retrieved documents, access to other information retrieval systems through gateways supporting a common command interface, and interfaces to word processing systems. The system's internal structure is based on a high-level data communications protocol linking the user interface, index processor, search processor, and other system modules. This allows them to be easily distributed in a multi- or specialized-processor configuration. It also allows new modules, such as a knowledge-based query reformulator, to be added. 15 references.

TopFed: TCGA tailored federated query processing and linking to LOD.

Science.gov (United States)

Saleem, Muhammad; Padmanabhuni, Shanmukha S; Ngomo, Axel-Cyrille Ngonga; Iqbal, Aftab; Almeida, Jonas S; Decker, Stefan; Deus, Helena F

2014-01-01

The Cancer Genome Atlas (TCGA) is a multidisciplinary, multi-institutional effort to catalogue genetic mutations responsible for cancer using genome analysis techniques. One of the aims of this project is to create a comprehensive and open repository of cancer related molecular analysis, to be exploited by bioinformaticians towards advancing cancer knowledge. However, devising bioinformatics applications to analyse such large dataset is still challenging, as it often requires downloading large archives and parsing the relevant text files. Therefore, it is making it difficult to enable virtual data integration in order to collect the critical co-variates necessary for analysis. We address these issues by transforming the TCGA data into the Semantic Web standard Resource Description Format (RDF), link it to relevant datasets in the Linked Open Data (LOD) cloud and further propose an efficient data distribution strategy to host the resulting 20.4 billion triples data via several SPARQL endpoints. Having the TCGA data distributed across multiple SPARQL endpoints, we enable biomedical scientists to query and retrieve information from these SPARQL endpoints by proposing a TCGA tailored federated SPARQL query processing engine named TopFed. We compare TopFed with a well established federation engine FedX in terms of source selection and query execution time by using 10 different federated SPARQL queries with varying requirements. Our evaluation results show that TopFed selects on average less than half of the sources (with 100% recall) with query execution time equal to one third to that of FedX. With TopFed, we aim to offer biomedical scientists a single-point-of-access through which distributed TCGA data can be accessed in unison. We believe the proposed system can greatly help researchers in the biomedical domain to carry out their research effectively with TCGA as the amount and diversity of data exceeds the ability of local resources to handle its retrieval and

Seasonal trends in tinnitus symptomatology: evidence from Internet search engine query data.

Science.gov (United States)

Plante, David T; Ingram, David G

2015-10-01

The primary aim of this study was to test the hypothesis that the symptom of tinnitus demonstrates a seasonal pattern with worsening in the winter relative to the summer using Internet search engine query data. Normalized search volume for the term 'tinnitus' from January 2004 through December 2013 was retrieved from Google Trends. Seasonal effects were evaluated using cosinor regression models. Primary countries of interest were the United States and Australia. Secondary exploratory analyses were also performed using data from Germany, the United Kingdom, Canada, Sweden, and Switzerland. Significant seasonal effects for 'tinnitus' search queries were found in the United States and Australia (p search volume in the winter relative to the summer. Our findings indicate that there are significant seasonal trends for Internet search queries for tinnitus, with a zenith in winter months. Further research is indicated to determine the biological mechanisms underlying these findings, as they may provide insights into the pathophysiology of this common and debilitating medical symptom.

Query by example video based on fuzzy c-means initialized by fixed clustering center

Science.gov (United States)

Hou, Sujuan; Zhou, Shangbo; Siddique, Muhammad Abubakar

2012-04-01

Currently, the high complexity of video contents has posed the following major challenges for fast retrieval: (1) efficient similarity measurements, and (2) efficient indexing on the compact representations. A video-retrieval strategy based on fuzzy c-means (FCM) is presented for querying by example. Initially, the query video is segmented and represented by a set of shots, each shot can be represented by a key frame, and then we used video processing techniques to find visual cues to represent the key frame. Next, because the FCM algorithm is sensitive to the initializations, here we initialized the cluster center by the shots of query video so that users could achieve appropriate convergence. After an FCM cluster was initialized by the query video, each shot of query video was considered a benchmark point in the aforesaid cluster, and each shot in the database possessed a class label. The similarity between the shots in the database with the same class label and benchmark point can be transformed into the distance between them. Finally, the similarity between the query video and the video in database was transformed into the number of similar shots. Our experimental results demonstrated the performance of this proposed approach.

Analysis of PubMed User Sessions Using a Full-Day PubMed Query Log: A Comparison of Experienced and Nonexperienced PubMed Users

Science.gov (United States)

2015-01-01

Background PubMed is the largest biomedical bibliographic information source on the Internet. PubMed has been considered one of the most important and reliable sources of up-to-date health care evidence. Previous studies examined the effects of domain expertise/knowledge on search performance using PubMed. However, very little is known about PubMed users’ knowledge of information retrieval (IR) functions and their usage in query formulation. Objective The purpose of this study was to shed light on how experienced/nonexperienced PubMed users perform their search queries by analyzing a full-day query log. Our hypotheses were that (1) experienced PubMed users who use system functions quickly retrieve relevant documents and (2) nonexperienced PubMed users who do not use them have longer search sessions than experienced users. Methods To test these hypotheses, we analyzed PubMed query log data containing nearly 3 million queries. User sessions were divided into two categories: experienced and nonexperienced. We compared experienced and nonexperienced users per number of sessions, and experienced and nonexperienced user sessions per session length, with a focus on how fast they completed their sessions. Results To test our hypotheses, we measured how successful information retrieval was (at retrieving relevant documents), represented as the decrease rates of experienced and nonexperienced users from a session length of 1 to 2, 3, 4, and 5. The decrease rate (from a session length of 1 to 2) of the experienced users was significantly larger than that of the nonexperienced groups. Conclusions Experienced PubMed users retrieve relevant documents more quickly than nonexperienced PubMed users in terms of session length. PMID:26139516

Learning to rank for information retrieval

CERN Document Server

Liu, Tie-Yan

2011-01-01

Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as coll

跨語言資訊檢索中查詢問題特性於檢索效益之影響 Influences of Query Characteristics to Retrieval Performance in Cross-Language Information Retrieval

Directory of Open Access Journals (Sweden)

Kuang-Hua Chen

2008-12-01

Full Text Available 本研究分別由查詢主題(Topic的文本特性、語言特性，及欄位特性等三個面向，檢視第六屆NTCIR資訊檢索評估會議之跨語言檢索評估項目的資料，試 圖找出查詢主題特性對檢索效益之影響。研究結果發現查詢主題的文本特性僅有「主題類別」對檢索效益具影響力，涵蓋地域、時間空間明確性，條件敘述明確性及 數量等對檢索效益沒有顯著差異；語言特性方面，以韓文表現最佳，表示在CLIR機制中，選用不同語言的問題集與文件集對於檢索效益的確會造成影響；欄位特 性方面，本研究發現不論選用標題(Title、簡短資訊需求(Description、詳細資訊需求(Narrative、相關概念 (Concepts為索引來源，不會造成明顯檢索效益的差異，但部分欄位的檢索效益確實比較好；在研究團隊與欄位特性及語言特性的交互作用的檢定，本研 究發現研究團隊與檢索欄位在檢索效益上有交互作用，也就是說研究團隊的不同與檢索欄位的不同對檢索效益會造成影響，而在語言組合的選擇上則無明顯的交互作 用。This study investigated the influences of structured query on retrieval performance from textual, linguistic, and fielded characteristics. The search runs of NCTIR-6 CLIR Task have been used as the targeted data for this study. The results concluded that only subject out of other textual characteristics demonstrated significant effects on retrieval performance; linguistic characteristics showed great impacts on retrieval performance; fielded information did not show significant effects on retrieval performance but some fielded information performed better than others. This study also made clear that there existed interactions between fielded information in queries and participating teams (consequently the retrieval techniques used by these teams but no significant interactions between linguistic

Information retrieval system based on INIS tapes

International Nuclear Information System (INIS)

Pultorak, G.

1976-01-01

An information retrieval system based on the INIS computer tapes is described. It includes the three main elements of a computerized information system: a data base on a machine -readable medium, a collection of queries which represent the information needs from the data - base, and a set of programs by which the actual retrieval is done, according to the user's queries. The system is built for the center's computer, a CDC 3600, and its special features characterize, to a certain degree, the structure of the programs. (author)

Manchester visual query language

Science.gov (United States)

Oakley, John P.; Davis, Darryl N.; Shann, Richard T.

1993-04-01

We report a database language for visual retrieval which allows queries on image feature information which has been computed and stored along with images. The language is novel in that it provides facilities for dealing with feature data which has actually been obtained from image analysis. Each line in the Manchester Visual Query Language (MVQL) takes a set of objects as input and produces another, usually smaller, set as output. The MVQL constructs are mainly based on proven operators from the field of digital image analysis. An example is the Hough-group operator which takes as input a specification for the objects to be grouped, a specification for the relevant Hough space, and a definition of the voting rule. The output is a ranked list of high scoring bins. The query could be directed towards one particular image or an entire image database, in the latter case the bins in the output list would in general be associated with different images. We have implemented MVQL in two layers. The command interpreter is a Lisp program which maps each MVQL line to a sequence of commands which are used to control a specialized database engine. The latter is a hybrid graph/relational system which provides low-level support for inheritance and schema evolution. In the paper we outline the language and provide examples of useful queries. We also describe our solution to the engineering problems associated with the implementation of MVQL.

Nonmaterialized Relations and the Support of Information Retrieval Applications by Relational Database Systems.

Science.gov (United States)

Lynch, Clifford A.

1991-01-01

Describes several aspects of the problem of supporting information retrieval system query requirements in the relational database management system (RDBMS) environment and proposes an extension to query processing called nonmaterialized relations. User interactions with information retrieval systems are discussed, and nonmaterialized relations are…

Development and evaluation of a geographic information retrieval system using fine grained toponyms

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Damien Palacio

2015-12-01

Full Text Available Geographic information retrieval (GIR is concerned with returning information in response to an information need, typically expressed in terms of a thematic and spatial component linked by a spatial relationship. However, evaluation initiatives have often failed to show significant differences between simple text baselines and more complex spatially enabled GIR approaches. We explore the effectiveness of three systems (a text baseline, spatial query expansion, and a full GIR system utilizing both text and spatial indexes at retrieving documents from a corpus describing mountaineering expeditions, centred around fine grained toponyms. To allow evaluation, we use user generated content (UGC in the form of metadata associated with individual articles to build a test collection of queries and judgments. The test collection allowed us to demonstrate that a GIR-based method significantly outperformed a text baseline for all but very specific queries associated with very small query radii. We argue that such approaches to test collection development have much to offer in the evaluation of GIR.

GeoVanet: A Routing Protocol for Query Processing in Vehicular Networks

Directory of Open Access Journals (Sweden)

Thierry Delot

2011-01-01

Full Text Available In a vehicular ad hoc network (VANET, cars can exchange information by using short-range wireless communications. Along with the opportunities offered by vehicular networks, a number of challenges also arise. In particular, most works so far have focused on a push model, where potentially useful data are pushed towards vehicles. The use of pull models, that would allow users to send queries to a set of cars in order to find the desired information, has not been studied in depth. The main challenge for pull models is the difficulty to route the different results towards the query originator in a highly dynamic network where the nodes move very quickly. To solve this issue, we propose GeoVanet, an anonymous and non-intrusive geographic routing protocol which ensures that the sender of a query can get a consistent answer. Our goal is to ensure that the user will be able to retrieve the query results within a bounded time. To prove the effectiveness of GeoVanet, an extensive experimental evaluation has been performed, that proves the interest of the proposal for both rural and urban areas. It shows that up to 80% of the available query results are delivered to the user.

Graphical modeling and query language for hospitals.

Science.gov (United States)

Barzdins, Janis; Barzdins, Juris; Rencis, Edgars; Sostaks, Agris

2013-01-01

So far there has been little evidence that implementation of the health information technologies (HIT) is leading to health care cost savings. One of the reasons for this lack of impact by the HIT likely lies in the complexity of the business process ownership in the hospitals. The goal of our research is to develop a business model-based method for hospital use which would allow doctors to retrieve directly the ad-hoc information from various hospital databases. We have developed a special domain-specific process modelling language called the MedMod. Formally, we define the MedMod language as a profile on UML Class diagrams, but we also demonstrate it on examples, where we explain the semantics of all its elements informally. Moreover, we have developed the Process Query Language (PQL) that is based on MedMod process definition language. The purpose of PQL is to allow a doctor querying (filtering) runtime data of hospital's processes described using MedMod. The MedMod language tries to overcome deficiencies in existing process modeling languages, allowing to specify the loosely-defined sequence of the steps to be performed in the clinical process. The main advantages of PQL are in two main areas - usability and efficiency. They are: 1) the view on data through "glasses" of familiar process, 2) the simple and easy-to-perceive means of setting filtering conditions require no more expertise than using spreadsheet applications, 3) the dynamic response to each step in construction of the complete query that shortens the learning curve greatly and reduces the error rate, and 4) the selected means of filtering and data retrieving allows to execute queries in O(n) time regarding the size of the dataset. We are about to continue developing this project with three further steps. First, we are planning to develop user-friendly graphical editors for the MedMod process modeling and query languages. The second step is to do evaluation of usability the proposed language and tool

Web information retrieval based on ontology

Science.gov (United States)

Zhang, Jian

2013-03-01

The purpose of the Information Retrieval (IR) is to find a set of documents that are relevant for a specific information need of a user. Traditional Information Retrieval model commonly used in commercial search engine is based on keyword indexing system and Boolean logic queries. One big drawback of traditional information retrieval is that they typically retrieve information without an explicitly defined domain of interest to the users so that a lot of no relevance information returns to users, which burden the user to pick up useful answer from these no relevance results. In order to tackle this issue, many semantic web information retrieval models have been proposed recently. The main advantage of Semantic Web is to enhance search mechanisms with the use of Ontology's mechanisms. In this paper, we present our approach to personalize web search engine based on ontology. In addition, key techniques are also discussed in our paper. Compared to previous research, our works concentrate on the semantic similarity and the whole process including query submission and information annotation.

A humming retrieval system based on music fingerprint

Science.gov (United States)

Han, Xingkai; Cao, Baiyu

2011-10-01

In this paper, we proposed an improved music information retrieval method utilizing the music fingerprint. The goal of this method is to represent the music with compressed musical information. Based on the selected MIDI files, which are generated automatically as our music target database, we evaluate the accuracy, effectiveness, and efficiency of this method. In this research we not only extract the feature sequence, which can represent the file effectively, from the query and melody database, but also make it possible for retrieving the results in an innovative way. We investigate on the influence of noise to the performance of our system. As experimental result shows, the retrieval accuracy arriving at up to91% without noise is pretty well

Performance evaluation of unified medical language system®'s synonyms expansion to query PubMed

Directory of Open Access Journals (Sweden)

Griffon Nicolas

2012-02-01

Full Text Available Abstract Background PubMed is the main access to medical literature on the Internet. In order to enhance the performance of its information retrieval tools, primarily non-indexed citations, the authors propose a method: expanding users' queries using Unified Medical Language System' (UMLS synonyms i.e. all the terms gathered under one unique Concept Unique Identifier. Methods This method was evaluated using queries constructed to emphasize the differences between this new method and the current PubMed automatic term mapping. Four experts assessed citation relevance. Results Using UMLS, we were able to retrieve new citations in 45.5% of queries, which implies a small increase in recall. The new strategy led to a heterogeneous 23.7% mean increase in non-indexed citation retrieved. Of these, 82% have been published less than 4 months earlier. The overall mean precision was 48.4% but differed according to the evaluators, ranging from 36.7% to 88.1% (Inter rater agreement was poor: kappa = 0.34. Conclusions This study highlights the need for specific search tools for each type of user and use-cases. The proposed strategy may be useful to retrieve recent scientific advancement.

To compare PubMed Clinical Queries and UpToDate in teaching information mastery to clinical residents: a crossover randomized controlled trial.

Science.gov (United States)

Sayyah Ensan, Ladan; Faghankhani, Masoomeh; Javanbakht, Anna; Ahmadi, Seyed-Foad; Baradaran, Hamid Reza

2011-01-01

To compare PubMed Clinical Queries and UpToDate regarding the amount and speed of information retrieval and users' satisfaction. A cross-over randomized trial was conducted in February 2009 in Tehran University of Medical Sciences that included 44 year-one or two residents who participated in an information mastery workshop. A one-hour lecture on the principles of information mastery was organized followed by self learning slide shows before using each database. Subsequently, participants were randomly assigned to answer 2 clinical scenarios using either UpToDate or PubMed Clinical Queries then crossed to use the other database to answer 2 different clinical scenarios. The proportion of relevantly answered clinical scenarios, time to answer retrieval, and users' satisfaction were measured in each database. Based on intention-to-treat analysis, participants retrieved the answer of 67 (76%) questions using UpToDate and 38 (43%) questions using PubMed Clinical Queries (PPubMed Clinical Queries (PPubMed Clinical Queries users (PPubmed Clinical Queries can lead to not only a higher proportion of relevant answer retrieval within a shorter time, but also a higher users' satisfaction. So, addition of tutoring pre-appraised sources such as UpToDate to the information mastery curricula seems to be highly efficient.

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.

Supporting Keyword Search for Image Retrieval with Integration of Probabilistic Annotation

Directory of Open Access Journals (Sweden)

Tie Hua Zhou

2015-05-01

Full Text Available The ever-increasing quantities of digital photo resources are annotated with enriching vocabularies to form semantic annotations. Photo-sharing social networks have boosted the need for efficient and intuitive querying to respond to user requirements in large-scale image collections. In order to help users formulate efficient and effective image retrieval, we present a novel integration of a probabilistic model based on keyword query architecture that models the probability distribution of image annotations: allowing users to obtain satisfactory results from image retrieval via the integration of multiple annotations. We focus on the annotation integration step in order to specify the meaning of each image annotation, thus leading to the most representative annotations of the intent of a keyword search. For this demonstration, we show how a probabilistic model has been integrated to semantic annotations to allow users to intuitively define explicit and precise keyword queries in order to retrieve satisfactory image results distributed in heterogeneous large data sources. Our experiments on SBU (collected by Stony Brook University database show that (i our integrated annotation contains higher quality representatives and semantic matches; and (ii the results indicating annotation integration can indeed improve image search result quality.

New Path Based Index Structure for Processing CAS Queries over XML Database

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Krishna Asawa

2017-01-01

Full Text Available Querying nested data has become one of the most challenging issues for retrieving desired information from the Web. Today diverse applications generate a tremendous amount of data in different formats. These data and information exchanged on the Web are commonly expressed as nested representation such as XML, JSON, etc. Unlike the traditional database system, they don't have a rigid schema. In general, the nested data is managed by storing data and its structures separately which significantly reduces the performance of data retrieving. Ensuring efficiency of processing queries which locates the exact positions of the elements has become a big challenging issue. There are different indexing structures which have been proposed in the literature to improve the performance of the query processing on the nested structure. Most of the past researches on nested structure concentrate on the structure alone. This paper proposes new index structure which combines siblings of the terminal nodes as one path which efficiently processes twig queries with less number of lookups and joins. The proposed approach is compared with some of the existing approaches. The results also show that they are processed with better performance compared to the existing ones.

Language model: Extension to solve inconsistency, incompleteness, and short query in cultural heritage collection

Science.gov (United States)

Tan, Kian Lam; Lim, Chen Kim

2017-10-01

With the explosive growth of online information such as email messages, news articles, and scientific literature, many institutions and museums are converting their cultural collections from physical data to digital format. However, this conversion resulted in the issues of inconsistency and incompleteness. Besides, the usage of inaccurate keywords also resulted in short query problem. Most of the time, the inconsistency and incompleteness are caused by the aggregation fault in annotating a document itself while the short query problem is caused by naive user who has prior knowledge and experience in cultural heritage domain. In this paper, we presented an approach to solve the problem of inconsistency, incompleteness and short query by incorporating the Term Similarity Matrix into the Language Model. Our approach is tested on the Cultural Heritage in CLEF (CHiC) collection which consists of short queries and documents. The results show that the proposed approach is effective and has improved the accuracy in retrieval time.

Cluster-based query expansion using external collections in medical information retrieval.

Science.gov (United States)

Oh, Heung-Seon; Jung, Yuchul

2015-12-01

Utilizing external collections to improve retrieval performance is challenging research because various test collections are created for different purposes. Improving medical information retrieval has also gained much attention as various types of medical documents have become available to researchers ever since they started storing them in machine processable formats. In this paper, we propose an effective method of utilizing external collections based on the pseudo relevance feedback approach. Our method incorporates the structure of external collections in estimating individual components in the final feedback model. Extensive experiments on three medical collections (TREC CDS, CLEF eHealth, and OHSUMED) were performed, and the results were compared with a representative expansion approach utilizing the external collections to show the superiority of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Method of and System for Information Retrieval

DEFF Research Database (Denmark)

2015-01-01

This invention relates to a system for and a method (100) of searching a collection of digital information (150) comprising a number of digital documents (110), the method comprising receiving or obtaining (102) a search query, the query comprising a number of search terms, searching (103) an ind......, a method of and a system for information retrieval or searching is readily provided that enhances the searching quality (i.e. the number of relevant documents retrieved and such documents being ranked high) when (also) using queries containing many search terms.......This invention relates to a system for and a method (100) of searching a collection of digital information (150) comprising a number of digital documents (110), the method comprising receiving or obtaining (102) a search query, the query comprising a number of search terms, searching (103) an index...... (300) using the search terms thereby providing information (301) about which digital documents (110) of the collection of digital information (150) that contains a given search term and one or more search related metrics (302; 303; 304; 305; 306), ranking (105) at least a part of the search result...

Google BigQuery analytics

CERN Document Server

Tigani, Jordan

2014-01-01

How to effectively use BigQuery, avoid common mistakes, and execute sophisticated queries against large datasets Google BigQuery Analytics is the perfect guide for business and data analysts who want the latest tips on running complex queries and writing code to communicate with the BigQuery API. The book uses real-world examples to demonstrate current best practices and techniques, and also explains and demonstrates streaming ingestion, transformation via Hadoop in Google Compute engine, AppEngine datastore integration, and using GViz with Tableau to generate charts of query results. In addit

Mathematical Formula Search using Natural Language Queries

Directory of Open Access Journals (Sweden)

YANG, S.

2014-11-01

Full Text Available This paper presents how to search mathematical formulae written in MathML when given plain words as a query. Since the proposed method allows natural language queries like the traditional Information Retrieval for the mathematical formula search, users do not need to enter any complicated math symbols and to use any formula input tool. For this, formula data is converted into plain texts, and features are extracted from the converted texts. In our experiments, we achieve an outstanding performance, a MRR of 0.659. In addition, we introduce how to utilize formula classification for formula search. By using class information, we finally achieve an improved performance, a MRR of 0.690.

Evaluation of Content-Matched Range Monitoring Queries over Moving Objects in Mobile Computing Environments.

Science.gov (United States)

Jung, HaRim; Song, MoonBae; Youn, Hee Yong; Kim, Ung Mo

2015-09-18

A content-matched (CM) rangemonitoring query overmoving objects continually retrieves the moving objects (i) whose non-spatial attribute values are matched to given non-spatial query values; and (ii) that are currently located within a given spatial query range. In this paper, we propose a new query indexing structure, called the group-aware query region tree (GQR-tree) for efficient evaluation of CMrange monitoring queries. The primary role of the GQR-tree is to help the server leverage the computational capabilities of moving objects in order to improve the system performance in terms of the wireless communication cost and server workload. Through a series of comprehensive simulations, we verify the superiority of the GQR-tree method over the existing methods.

Evaluation of Content-Matched Range Monitoring Queries over Moving Objects in Mobile Computing Environments

Directory of Open Access Journals (Sweden)

HaRim Jung

2015-09-01

Full Text Available A content-matched (CM rangemonitoring query overmoving objects continually retrieves the moving objects (i whose non-spatial attribute values are matched to given non-spatial query values; and (ii that are currently located within a given spatial query range. In this paper, we propose a new query indexing structure, called the group-aware query region tree (GQR-tree for efficient evaluation of CMrange monitoring queries. The primary role of the GQR-tree is to help the server leverage the computational capabilities of moving objects in order to improve the system performance in terms of the wireless communication cost and server workload. Through a series of comprehensive simulations, we verify the superiority of the GQR-tree method over the existing methods.

Advanced SPARQL querying in small molecule databases.

Science.gov (United States)

Galgonek, Jakub; Hurt, Tomáš; Michlíková, Vendula; Onderka, Petr; Schwarz, Jan; Vondrášek, Jiří

2016-01-01

In recent years, the Resource Description Framework (RDF) and the SPARQL query language have become more widely used in the area of cheminformatics and bioinformatics databases. These technologies allow better interoperability of various data sources and powerful searching facilities. However, we identified several deficiencies that make usage of such RDF databases restrictive or challenging for common users. We extended a SPARQL engine to be able to use special procedures inside SPARQL queries. This allows the user to work with data that cannot be simply precomputed and thus cannot be directly stored in the database. We designed an algorithm that checks a query against data ontology to identify possible user errors. This greatly improves query debugging. We also introduced an approach to visualize retrieved data in a user-friendly way, based on templates describing visualizations of resource classes. To integrate all of our approaches, we developed a simple web application. Our system was implemented successfully, and we demonstrated its usability on the ChEBI database transformed into RDF form. To demonstrate procedure call functions, we employed compound similarity searching based on OrChem. The application is publicly available at https://bioinfo.uochb.cas.cz/projects/chemRDF.

References and arrow notation instead of join operation in query languages

Directory of Open Access Journals (Sweden)

Alexandr Savinov

2012-10-01

Full Text Available We study properties of the join operation in query languages and describe some of its major drawbacks. We provide strong arguments against using joins as a main construct for retrieving related data elements in general purpose query languages and argue for using references instead. Since conventional references are quite restrictive when applied to data modeling and query languages, we propose to use generalized references as they are defined in the concept-oriented model (COM. These references are used by two new operations, called projection and de-projection, which are denoted by right and left arrows and therefore this access method is referred to as arrow notation. We demonstrate advantages of the arrow notation in comparison to joins and argue that it makes queries simpler, more natural, easier to understand, and the whole query writing process more productive and less error-prone.

TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu

2016-06-25

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

TRIP: An interactive retrieving-inferring data imputation approach

KAUST Repository

Li, Zhixu; Qin, Lu; Cheng, Hong; Zhang, Xiangliang; Zhou, Xiaofang

2016-01-01

Data imputation aims at filling in missing attribute values in databases. Existing imputation approaches to nonquantitive string data can be roughly put into two categories: (1) inferring-based approaches [2], and (2) retrieving-based approaches [1]. Specifically, the inferring-based approaches find substitutes or estimations for the missing ones from the complete part of the data set. However, they typically fall short in filling in unique missing attribute values which do not exist in the complete part of the data set [1]. The retrieving-based approaches resort to external resources for help by formulating proper web search queries to retrieve web pages containing the missing values from the Web, and then extracting the missing values from the retrieved web pages [1]. This webbased retrieving approach reaches a high imputation precision and recall, but on the other hand, issues a large number of web search queries, which brings a large overhead [1]. © 2016 IEEE.

GeoSpark SQL: An Effective Framework Enabling Spatial Queries on Spark

Directory of Open Access Journals (Sweden)

Zhou Huang

2017-09-01

Full Text Available In the era of big data, Internet-based geospatial information services such as various LBS apps are deployed everywhere, followed by an increasing number of queries against the massive spatial data. As a result, the traditional relational spatial database (e.g., PostgreSQL with PostGIS and Oracle Spatial cannot adapt well to the needs of large-scale spatial query processing. Spark is an emerging outstanding distributed computing framework in the Hadoop ecosystem. This paper aims to address the increasingly large-scale spatial query-processing requirement in the era of big data, and proposes an effective framework GeoSpark SQL, which enables spatial queries on Spark. On the one hand, GeoSpark SQL provides a convenient SQL interface; on the other hand, GeoSpark SQL achieves both efficient storage management and high-performance parallel computing through integrating Hive and Spark. In this study, the following key issues are discussed and addressed: (1 storage management methods under the GeoSpark SQL framework, (2 the spatial operator implementation approach in the Spark environment, and (3 spatial query optimization methods under Spark. Experimental evaluation is also performed and the results show that GeoSpark SQL is able to achieve real-time query processing. It should be noted that Spark is not a panacea. It is observed that the traditional spatial database PostGIS/PostgreSQL performs better than GeoSpark SQL in some query scenarios, especially for the spatial queries with high selectivity, such as the point query and the window query. In general, GeoSpark SQL performs better when dealing with compute-intensive spatial queries such as the kNN query and the spatial join query.

ImageGrouper: a group-oriented user interface for content-based image retrieval and digital image arrangement

NARCIS (Netherlands)

Nakazato, Munehiro; Manola, L.; Huang, Thomas S.

In content-based image retrieval (CBIR), experimental (trial-and-error) query with relevance feedback is essential for successful retrieval. Unfortunately, the traditional user interfaces are not suitable for trying different combinations of query examples. This is because first, these systems

Software Helps Retrieve Information Relevant to the User

Science.gov (United States)

Mathe, Natalie; Chen, James

2003-01-01

The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

Data Discretization for Novel Relationship Discovery in Information Retrieval.

Science.gov (United States)

Benoit, G.

2002-01-01

Describes an information retrieval, visualization, and manipulation model which offers the user multiple ways to exploit the retrieval set, based on weighted query terms, via an interactive interface. Outlines the mathematical model and describes an information retrieval application built on the model to search structured and full-text files.…

Mammogram retrieval through machine learning within BI-RADS standards.

Science.gov (United States)

Wei, Chia-Hung; Li, Yue; Huang, Pai Jung

2011-08-01

A content-based mammogram retrieval system can support usual comparisons made on images by physicians, answering similarity queries over images stored in the database. The importance of searching for similar mammograms lies in the fact that physicians usually try to recall similar cases by seeking images that are pathologically similar to a given image. This paper presents a content-based mammogram retrieval system, which employs a query example to search for similar mammograms in the database. In this system the mammographic lesions are interpreted based on their medical characteristics specified in the Breast Imaging Reporting and Data System (BI-RADS) standards. A hierarchical similarity measurement scheme based on a distance weighting function is proposed to model user's perception and maximizes the effectiveness of each feature in a mammographic descriptor. A machine learning approach based on support vector machines and user's relevance feedback is also proposed to analyze the user's information need in order to retrieve target images more accurately. Experimental results demonstrate that the proposed machine learning approach with Radial Basis Function (RBF) kernel function achieves the best performance among all tested ones. Furthermore, the results also show that the proposed learning approach can improve retrieval performance when applied to retrieve mammograms with similar mass and calcification lesions, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

Using Bitmap Indexing Technology for Combined Numerical and TextQueries

Energy Technology Data Exchange (ETDEWEB)

Stockinger, Kurt; Cieslewicz, John; Wu, Kesheng; Rotem, Doron; Shoshani, Arie

2006-10-16

In this paper, we describe a strategy of using compressedbitmap indices to speed up queries on both numerical data and textdocuments. By using an efficient compression algorithm, these compressedbitmap indices are compact even for indices with millions of distinctterms. Moreover, bitmap indices can be used very efficiently to answerBoolean queries over text documents involving multiple query terms.Existing inverted indices for text searches are usually inefficient forcorpora with a very large number of terms as well as for queriesinvolving a large number of hits. We demonstrate that our compressedbitmap index technology overcomes both of those short-comings. In aperformance comparison against a commonly used database system, ourindices answer queries 30 times faster on average. To provide full SQLsupport, we integrated our indexing software, called FastBit, withMonetDB. The integrated system MonetDB/FastBit provides not onlyefficient searches on a single table as FastBit does, but also answersjoin queries efficiently. Furthermore, MonetDB/FastBit also provides avery efficient retrieval mechanism of result records.

Monet: a next-generation database kernel for query-intensive applications

NARCIS (Netherlands)

P.A. Boncz (Peter)

2002-01-01

htmlabstractMonet is a database kernel targeted at query-intensive, heavy analysis applications (the opposite of transaction processing), which include OLAP and data mining, but also go beyond the business domain in GIS processing, multi-media retrieval and XML. The clean sheet approach of Monet

Improving Web Page Retrieval using Search Context from Clicked Domain Names

NARCIS (Netherlands)

Li, R.

Search context is a crucial factor that helps to understand a user’s information need in ad-hoc Web page retrieval. A query log of a search engine contains rich information on issued queries and their corresponding clicked Web pages. The clicked data implies its relevance to the query and can be

Medical Information Retrieval Enhanced with User's Query Expanded with Tag-Neighbors

DEFF Research Database (Denmark)

Durao, Frederico; Bayyapu, Karunakar Reddy; Xu, Guandong

2013-01-01

Under-specified queries often lead to undesirable search results that do not contain the information needed. This problem gets worse when it comes to medical information, a natural human demand everywhere. Existing search engines on the Web often are unable to handle medical search well because...

QueryArch3D: Querying and Visualising 3D Models of a Maya Archaeological Site in a Web-Based Interface

Directory of Open Access Journals (Sweden)

Giorgio Agugiaro

2011-12-01

Full Text Available Constant improvements in the field of surveying, computing and distribution of digital-content are reshaping the way Cultural Heritage can be digitised and virtually accessed, even remotely via web. A traditional 2D approach for data access, exploration, retrieval and exploration may generally suffice, however more complex analyses concerning spatial and temporal features require 3D tools, which, in some cases, have not yet been implemented or are not yet generally commercially available. Efficient organisation and integration strategies applicable to the wide array of heterogeneous data in the field of Cultural Heritage represent a hot research topic nowadays. This article presents a visualisation and query tool (QueryArch3D conceived to deal with multi-resolution 3D models. Geometric data are organised in successive levels of detail (LoD, provided with geometric and semantic hierarchies and enriched with attributes coming from external data sources. The visualisation and query front-end enables the 3D navigation of the models in a virtual environment, as well as the interaction with the objects by means of queries based on attributes or on geometries. The tool can be used as a standalone application, or served through the web. The characteristics of the research work, along with some implementation issues and the developed QueryArch3D tool will be discussed and presented.

Query-Biased Preview over Outsourced and Encrypted Data

Directory of Open Access Journals (Sweden)

Ningduo Peng

2013-01-01

document to check if it contains the desired content. An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document. However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge. Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each document, the scheme has O(d storage complexity and O(log(d/s+s+d/s communication complexity, where d is the document size and s is the snippet length.

Retrieval of very large numbers of items in the Web of Science: an exercise to develop accurate search strategies

NARCIS (Netherlands)

Arencibia-Jorge, R.; Leydesdorff, L.; Chinchilla-Rodríguez, Z.; Rousseau, R.; Paris, S.W.

2009-01-01

The Web of Science interface counts at most 100,000 retrieved items from a single query. If the query results in a dataset containing more than 100,000 items the number of retrieved items is indicated as >100,000. The problem studied here is how to find the exact number of items in a query that

A web-based data-querying tool based on ontology-driven methodology and flowchart-based model.

Science.gov (United States)

Ping, Xiao-Ou; Chung, Yufang; Tseng, Yi-Ju; Liang, Ja-Der; Yang, Pei-Ming; Huang, Guan-Tarn; Lai, Feipei

2013-10-08

Because of the increased adoption rate of electronic medical record (EMR) systems, more health care records have been increasingly accumulating in clinical data repositories. Therefore, querying the data stored in these repositories is crucial for retrieving the knowledge from such large volumes of clinical data. The aim of this study is to develop a Web-based approach for enriching the capabilities of the data-querying system along the three following considerations: (1) the interface design used for query formulation, (2) the representation of query results, and (3) the models used for formulating query criteria. The Guideline Interchange Format version 3.5 (GLIF3.5), an ontology-driven clinical guideline representation language, was used for formulating the query tasks based on the GLIF3.5 flowchart in the Protégé environment. The flowchart-based data-querying model (FBDQM) query execution engine was developed and implemented for executing queries and presenting the results through a visual and graphical interface. To examine a broad variety of patient data, the clinical data generator was implemented to automatically generate the clinical data in the repository, and the generated data, thereby, were employed to evaluate the system. The accuracy and time performance of the system for three medical query tasks relevant to liver cancer were evaluated based on the clinical data generator in the experiments with varying numbers of patients. In this study, a prototype system was developed to test the feasibility of applying a methodology for building a query execution engine using FBDQMs by formulating query tasks using the existing GLIF. The FBDQM-based query execution engine was used to successfully retrieve the clinical data based on the query tasks formatted using the GLIF3.5 in the experiments with varying numbers of patients. The accuracy of the three queries (ie, "degree of liver damage," "degree of liver damage when applying a mutually exclusive setting

NoSQL: collection document and cloud by using a dynamic web query form

Science.gov (United States)

Abdalla, Hemn B.; Lin, Jinzhao; Li, Guoquan

2015-07-01

Mongo-DB (from "humongous") is an open-source document database and the leading NoSQL database. A NoSQL (Not Only SQL, next generation databases, being non-relational, deal, open-source and horizontally scalable) presenting a mechanism for storage and retrieval of documents. Previously, we stored and retrieved the data using the SQL queries. Here, we use the MonogoDB that means we are not utilizing the MySQL and SQL queries. Directly importing the documents into our Drives, retrieving the documents on that drive by not applying the SQL queries, using the IO BufferReader and Writer, BufferReader for importing our type of document files to my folder (Drive). For retrieving the document files, the usage is BufferWriter from the particular folder (or) Drive. In this sense, providing the security for those storing files for what purpose means if we store the documents in our local folder means all or views that file and modified that file. So preventing that file, we are furnishing the security. The original document files will be changed to another format like in this paper; Binary format is used. Our documents will be converting to the binary format after that direct storing in one of our folder, that time the storage space will provide the private key for accessing that file. Wherever any user tries to discover the Document files means that file data are in the binary format, the document's file owner simply views that original format using that personal key from receive the secret key from the cloud.

KoralQuery -- A General Corpus Query Protocol

DEFF Research Database (Denmark)

Bingel, Joachim; Diewald, Nils

2015-01-01

. In this paper, we present KoralQuery, a JSON-LD based general corpus query protocol, aiming to be independent of particular QLs, tasks and corpus formats. In addition to describing the system of types and operations that KoralQuery is built on, we exemplify the representation of corpus queries in the serialized...

Using pattern structures to support information retrieval with Formal Concept Analysis

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Astudillo , Hernan; Napoli , Amedeo

2013-01-01

International audience; In this paper we introduce a novel approach to information retrieval (IR) based on Formal Concept Analysis (FCA). The use of concept lattices to support the task of document retrieval in IR has proven effective since they allow querying in the space of terms modelled by concept intents and navigation in the space of documents modelled by concept extents. However, current approaches use binary representations to illustrate the relations between documents and terms (''do...

Content-Based Image Retrieval Based on Electromagnetism-Like Mechanism

Directory of Open Access Journals (Sweden)

Hamid A. Jalab

2013-01-01

Full Text Available Recently, many researchers in the field of automatic content-based image retrieval have devoted a remarkable amount of research looking for methods to retrieve the best relevant images to the query image. This paper presents a novel algorithm for increasing the precision in content-based image retrieval based on electromagnetism optimization technique. The electromagnetism optimization is a nature-inspired technique that follows the collective attraction-repulsion mechanism by considering each image as an electrical charge. The algorithm is composed of two phases: fitness function measurement and electromagnetism optimization technique. It is implemented on a database with 8,000 images spread across 80 classes with 100 images in each class. Eight thousand queries are fired on the database, and the overall average precision is computed. Experimental results of the proposed approach have shown significant improvement in the retrieval performance in regard to precision.

A Distributed Approach to Continuous Monitoring of Constrained k-Nearest Neighbor Queries in Road Networks

Directory of Open Access Journals (Sweden)

Hyung-Ju Cho

2012-01-01

Full Text Available Given two positive parameters k and r, a constrained k-nearest neighbor (CkNN query returns the k closest objects within a network distance r of the query location in road networks. In terms of the scalability of monitoring these CkNN queries, existing solutions based on central processing at a server suffer from a sudden and sharp rise in server load as well as messaging cost as the number of queries increases. In this paper, we propose a distributed and scalable scheme called DAEMON for the continuous monitoring of CkNN queries in road networks. Our query processing is distributed among clients (query objects and server. Specifically, the server evaluates CkNN queries issued at intersections of road segments, retrieves the objects on the road segments between neighboring intersections, and sends responses to the query objects. Finally, each client makes its own query result using this server response. As a result, our distributed scheme achieves close-to-optimal communication costs and scales well to large numbers of monitoring queries. Exhaustive experimental results demonstrate that our scheme substantially outperforms its competitor in terms of query processing time and messaging cost.

Fuzzy Information Retrieval Using Genetic Algorithms and Relevance Feedback.

Science.gov (United States)

Petry, Frederick E.; And Others

1993-01-01

Describes an approach that combines concepts from information retrieval, fuzzy set theory, and genetic programing to improve weighted Boolean query formulation via relevance feedback. Highlights include background on information retrieval systems; genetic algorithms; subproblem formulation; and preliminary results based on a testbed. (Contains 12…

UCLA at TREC 2014 Clinical Decision Support Track: Exploring Language Models, Query Expansion, and Boosting

Science.gov (United States)

2014-11-01

qualitative benet to the retrieved results compared to lower and higher boost factors. 3 Query terms Comments right lower quadrant abdominal pain ... pain for hours, decreased appetite, and enlarged appendix on abdominal ultrasound. Table 1 describes the query terms for an example patient summary. The...the diagnostic process. For example, pediatric cases, women of child- bearing age, and geriatic populations each have a distinct set of possible

Vague element selection and query rewriting for XML retrieval

NARCIS (Netherlands)

Mihajlovic, V.; Hiemstra, Djoerd; Blok, H.E.; de Jong, Franciska M.G.; Kraaij, W.

In this paper we present the extension of our prototype three-level database system (TIJAH) developed for structured information retrieval. The extension is aimed at modeling vague search on XML elements. All three levels (conceptual, logical, and physical) of the TIJAH system are enhanced to

Salton and Buckley’s Landmark Research in Experimental Text Information Retrieval. A Review of: Salton, G., & Buckley, C. (1990. Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science, 41(4, 288–297.

Directory of Open Access Journals (Sweden)

Christine F. Marton

2011-01-01

Full Text Available Objectives – To compare the performance of the vector space model and the probabilistic weighting model of relevance feedback for the overall purpose of determining the most useful relevance feedback procedures. The amount of improvement that can be obtained from searching several test document collections with only one feedback iteration of each relevance feedback model was measured.Design – The experimental design consisted of 72 different tests: 2 different relevance feedback methods, each with 6 permutations, on 6 test document collections of various sizes. A residual collection method was utilized to ascertain the “true advantage provided by the relevance feedback process.” (Salton & Buckley, 1990, p. 293Setting – Department of Computer Science at Cornell University.Subjects – Six test document collections.Methods – Relevance feedback is an effective technique for query modification that provides significant improvement in search performance. Relevance feedback entails both “term reweighting,” the modification of term weights based on term use in retrieved relevant and non-relevant documents, and “query expansion,” which is the addition of new terms from relevant documents retrieved (Harman, 1992. Salton and Buckley (1990 evaluated two established relevance feedback models based on the vector space model (a spatial model and the probabilistic model, respectively. Harman (1992 describes the two key differences between these competing models of relevance feedback.[The vector space model merges] document vectors and original query vectors. This automatically reweights query terms by adding the weights from the actual occurrence of those query terms in the relevant documents, and subtracting the weights of those terms occurring in the non-relevant documents. Queries are automatically expanded by adding all the terms not in the original query that are in the relevant documents and non-relevant documents. They are expanded

An integrated information retrieval and document management system

Science.gov (United States)

Coles, L. Stephen; Alvarez, J. Fernando; Chen, James; Chen, William; Cheung, Lai-Mei; Clancy, Susan; Wong, Alexis

1993-01-01

This paper describes the requirements and prototype development for an intelligent document management and information retrieval system that will be capable of handling millions of pages of text or other data. Technologies for scanning, Optical Character Recognition (OCR), magneto-optical storage, and multiplatform retrieval using a Standard Query Language (SQL) will be discussed. The semantic ambiguity inherent in the English language is somewhat compensated-for through the use of coefficients or weighting factors for partial synonyms. Such coefficients are used both for defining structured query trees for routine queries and for establishing long-term interest profiles that can be used on a regular basis to alert individual users to the presence of relevant documents that may have just arrived from an external source, such as a news wire service. Although this attempt at evidential reasoning is limited in comparison with the latest developments in AI Expert Systems technology, it has the advantage of being commercially available.

Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

Directory of Open Access Journals (Sweden)

Kompatsiaris Ioannis

2004-01-01

Full Text Available An image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions and endow the indexing and retrieval system with content-based functionalities. Low-level descriptors for the color, position, size, and shape of each region are subsequently extracted. These arithmetic descriptors are automatically associated with appropriate qualitative intermediate-level descriptors, which form a simple vocabulary termed object ontology. The object ontology is used to allow the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword and their relations in a human-centered fashion. When querying for a specific semantic object (or objects, the intermediate-level descriptor values associated with both the semantic object and all image regions in the collection are initially compared, resulting in the rejection of most image regions as irrelevant. Following that, a relevance feedback mechanism, based on support vector machines and using the low-level descriptors, is invoked to rank the remaining potentially relevant image regions and produce the final query results. Experimental results and comparisons demonstrate, in practice, the effectiveness of our approach.

From Questions to Queries

Directory of Open Access Journals (Sweden)

M. Drlík

2007-12-01

Full Text Available The extension of (Internet databases forceseveryone to become more familiar with techniques of datastorage and retrieval because users’ success often dependson their ability to pose right questions and to be able tointerpret their answers. University programs pay moreattention to developing database programming skills than todata exploitation skills. To educate our students to become“database users”, the authors intensively exploit supportivetools simplifying the production of database elements astables, queries, forms, reports, web pages, and macros.Videosequences demonstrating “standard operations” forcompleting them have been prepared to enhance out-ofclassroomlearning. The use of SQL and other professionaltools is reduced to the cases when the wizards are unable togenerate the intended construct.

Improving accuracy for identifying related PubMed queries by an integrated approach.

Science.gov (United States)

Lu, Zhiyong; Wilbur, W John

2009-10-01

PubMed is the most widely used tool for searching biomedical literature online. As with many other online search tools, a user often types a series of multiple related queries before retrieving satisfactory results to fulfill a single information need. Meanwhile, it is also a common phenomenon to see a user type queries on unrelated topics in a single session. In order to study PubMed users' search strategies, it is necessary to be able to automatically separate unrelated queries and group together related queries. Here, we report a novel approach combining both lexical and contextual analyses for segmenting PubMed query sessions and identifying related queries and compare its performance with the previous approach based solely on concept mapping. We experimented with our integrated approach on sample data consisting of 1539 pairs of consecutive user queries in 351 user sessions. The prediction results of 1396 pairs agreed with the gold-standard annotations, achieving an overall accuracy of 90.7%. This demonstrates that our approach is significantly better than the previously published method. By applying this approach to a one day query log of PubMed, we found that a significant proportion of information needs involved more than one PubMed query, and that most of the consecutive queries for the same information need are lexically related. Finally, the proposed PubMed distance is shown to be an accurate and meaningful measure for determining the contextual similarity between biological terms. The integrated approach can play a critical role in handling real-world PubMed query log data as is demonstrated in our experiments.

An Intelligent System for Document Retrieval in Distributed Office Environments.

Science.gov (United States)

Mukhopadhyay, Uttam; And Others

1986-01-01

MINDS (Multiple Intelligent Node Document Servers) is a distributed system of knowledge-based query engines for efficiently retrieving multimedia documents in an office environment of distributed workstations. By learning document distribution patterns and user interests and preferences during system usage, it customizes document retrievals for…

Music Retrieval Based on the Relation between Color Association and Lyrics

Science.gov (United States)

Nakamur, Tetsuaki; Utsumi, Akira; Sakamoto, Maki

Various methods for music retrieval have been proposed. Recently, many researchers are tackling developing methods based on the relationship between music and feelings. In our previous psychological study, we found that there was a significant correlation between colors evoked from songs and colors evoked only from lyrics, and showed that the music retrieval system using lyrics could be developed. In this paper, we focus on the relationship among music, lyrics and colors, and propose a music retrieval method using colors as queries and analyzing lyrics. This method estimates colors evoked from songs by analyzing lyrics of the songs. On the first step of our method, words associated with colors are extracted from lyrics. We assumed two types of methods to extract words associated with colors. In the one of two methods, the words are extracted based on the result of a psychological experiment. In the other method, in addition to the words extracted based on the result of the psychological experiment, the words from corpora for the Latent Semantic Analysis are extracted. On the second step, colors evoked from the extracted words are compounded, and the compounded colors are regarded as those evoked from the song. On the last step, colors as queries are compared with colors estimated from lyrics, and the list of songs is presented based on similarities. We evaluated the two methods described above and found that the method based on the psychological experiment and corpora performed better than the method only based on the psychological experiment. As a result, we showed that the method using colors as queries and analyzing lyrics is effective for music retrieval.

Agricultural Library Information Retrieval Based on Improved Semantic Algorithm

OpenAIRE

Meiling , Xie

2014-01-01

International audience; To support users to quickly access information they need from the agricultural library’s vast information and to improve the low intelligence query service, a model for intelligent library information retrieval was constructed. The semantic web mode was introduced and the information retrieval framework was designed. The model structure consisted of three parts: Information data integration, user interface and information retrieval match. The key method supporting retr...

A Prototype of an Intelligent System for Information Retrieval: IOTA.

Science.gov (United States)

Chiaramella, Y.; Defude, B.

1987-01-01

Discusses expert systems and their value as components of information retrieval systems related to semantic inference, and describes IOTA, a model of an intelligent information retrieval system which emphasizes natural language query processing. Experimental results are discussed and current and future developments are highlighted. (Author/LRW)

On-Demand Associative Cross-Language Information Retrieval

Science.gov (United States)

Geraldo, André Pinto; Moreira, Viviane P.; Gonçalves, Marcos A.

This paper proposes the use of algorithms for mining association rules as an approach for Cross-Language Information Retrieval. These algorithms have been widely used to analyse market basket data. The idea is to map the problem of finding associations between sales items to the problem of finding term translations over a parallel corpus. The proposal was validated by means of experiments using queries in two distinct languages: Portuguese and Finnish to retrieve documents in English. The results show that the performance of our proposed approach is comparable to the performance of the monolingual baseline and to query translation via machine translation, even though these systems employ more complex Natural Language Processing techniques. The combination between machine translation and our approach yielded the best results, even outperforming the monolingual baseline.

Lower-Cost ∈-Private Information Retrieval

Directory of Open Access Journals (Sweden)

Toledo Raphael R.

2016-10-01

Full Text Available Private Information Retrieval (PIR, despite being well studied, is computationally costly and arduous to scale. We explore lower-cost relaxations of information-theoretic PIR, based on dummy queries, sparse vectors, and compositions with an anonymity system. We prove the security of each scheme using a flexible differentially private definition for private queries that can capture notions of imperfect privacy. We show that basic schemes are weak, but some of them can be made arbitrarily safe by composing them with large anonymity systems.

Design and development of semantic web-based system for computer science domain-specific information retrieval

Directory of Open Access Journals (Sweden)

Ritika Bansal

2016-09-01

Full Text Available In semantic web-based system, the concept of ontology is used to search results by contextual meaning of input query instead of keyword matching. From the research literature, there seems to be a need for a tool which can provide an easy interface for complex queries in natural language that can retrieve the domain-specific information from the ontology. This research paper proposes an IRSCSD system (Information retrieval system for computer science domain as a solution. This system offers advanced querying and browsing of structured data with search results automatically aggregated and rendered directly in a consistent user-interface, thus reducing the manual effort of users. So, the main objective of this research is design and development of semantic web-based system for integrating ontology towards domain-specific retrieval support. Methodology followed is a piecemeal research which involves the following stages. First Stage involves the designing of framework for semantic web-based system. Second stage builds the prototype for the framework using Protégé tool. Third Stage deals with the natural language query conversion into SPARQL query language using Python-based QUEPY framework. Fourth Stage involves firing of converted SPARQL queries to the ontology through Apache's Jena API to fetch the results. Lastly, evaluation of the prototype has been done in order to ensure its efficiency and usability. Thus, this research paper throws light on framework development for semantic web-based system that assists in efficient retrieval of domain-specific information, natural language query interpretation into semantic web language, creation of domain-specific ontology and its mapping with related ontology. This research paper also provides approaches and metrics for ontology evaluation on prototype ontology developed to study the performance based on accessibility of required domain-related information.

Coaching the exploration and exploitation in active learning for interactive video retrieval.

Science.gov (United States)

Wei, Xiao-Yong; Yang, Zhen-Qun

2013-03-01

Conventional active learning approaches for interactive video/image retrieval usually assume the query distribution is unknown, as it is difficult to estimate with only a limited number of labeled instances available. Thus, it is easy to put the system in a dilemma whether to explore the feature space in uncertain areas for a better understanding of the query distribution or to harvest in certain areas for more relevant instances. In this paper, we propose a novel approach called coached active learning that makes the query distribution predictable through training and, therefore, avoids the risk of searching on a completely unknown space. The estimated distribution, which provides a more global view of the feature space, can be used to schedule not only the timing but also the step sizes of the exploration and the exploitation in a principled way. The results of the experiments on a large-scale data set from TRECVID 2005-2009 validate the efficiency and effectiveness of our approach, which demonstrates an encouraging performance when facing domain-shift, outperforms eight conventional active learning methods, and shows superiority to six state-of-the-art interactive video retrieval systems.

Information Retrieval and Graph Analysis Approaches for Book Recommendation

OpenAIRE

Chahinez Benkoussas; Patrice Bellot

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval ...

A model for information retrieval driven by conceptual spaces

OpenAIRE

Tanase, D.

2015-01-01

A retrieval model describes the transformation of a query into a set of documents. The question is: what drives this transformation? For semantic information retrieval type of models this transformation is driven by the content and structure of the semantic models. In this case, Knowledge Organization Systems (KOSs) are the semantic models that encode the meaning employed for monolingual and cross-language retrieval. The focus of this research is the relationship between these meanings’ repre...

Harvesting All Matching Information To A Given Query From a Deep Website

NARCIS (Netherlands)

Khelghati, Mohammadreza; Hiemstra, Djoerd; van Keulen, Maurice; Armano, Giuliano; Bozzon, Alessandro; Giuliani, Alessandro

In this paper, the goal is harvesting all documents matching a given (entity) query from a deep web source. The objective is to retrieve all information about for instance "Denzel Washington", "Iran Nuclear Deal", or "FC Barcelona" from data hidden behind web forms. Policies of web search engines

Compounds in dictionary-based Cross-language information retrieval_revised

Directory of Open Access Journals (Sweden)

2002-01-01

Full Text Available Compound words form an important part of natural language. From the cross-lingual information retrieval (CLIR point of view it is important that many natural languages are highly productive with compounds, and translation resources cannot include entries for all compounds. Also, compounds are often content bearing words in a sentence. In Swedish, German and Finnish roughly one tenth of the words in a text prepared for information retrieval purposes are compounds. Important research questions concerning compound handling in dictionary-based cross-language information retrieval are 1 compound splitting into components, 2 normalisation of components, 3 translation of components and 4 query structuring for compounds and their components in the target language. The impact of compound processing on the performance of the cross-language information retrieval process is evaluated in this study and the results indicate that the effect is clearly positive.

Improve Biomedical Information Retrieval using Modified Learning to Rank Methods.

Science.gov (United States)

Xu, Bo; Lin, Hongfei; Lin, Yuan; Ma, Yunlong; Yang, Liang; Wang, Jian; Yang, Zhihao

2016-06-14

In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the problem automatically, providing users with the needed information. However, it is a great challenge to apply these technologies directly for biomedical retrieval, because of the abundance of domain specific terminologies. To enhance biomedical retrieval, we propose a novel framework based on learning to rank. Learning to rank is a series of state-of-the-art information retrieval techniques, and has been proved effective in many information retrieval tasks. In the proposed framework, we attempt to tackle the problem of the abundance of terminologies by constructing ranking models, which focus on not only retrieving the most relevant documents, but also diversifying the searching results to increase the completeness of the resulting list for a given query. In the model training, we propose two novel document labeling strategies, and combine several traditional retrieval models as learning features. Besides, we also investigate the usefulness of different learning to rank approaches in our framework. Experimental results on TREC Genomics datasets demonstrate the effectiveness of our framework for biomedical information retrieval.

Intelligent retrieval of chest X-ray image database using sketches

International Nuclear Information System (INIS)

Hasegawa, Jun-ichi; Okada, Noritake; Toriwaki, Jun-ichiro

1988-01-01

This paper presents further experiments on intelligent retrieval in our chest X-ray image database system using 'sketches'. First, in the previous sketch extraction procedure, vertical-location-invariant thresholding and shape-oriented smoothing are newly developed to improve the precision of lung borders and rib images in each sketch, respectively. Then, two new ways for image retrieval using sketches; (1) image-description retrieval and (2) pattern-matching retrieval, are proposed. In each retrieval way, a procedure for understanding picture queries input through a sketch is described in detail. (author)

Content-based video retrieval by example video clip

Science.gov (United States)

Dimitrova, Nevenka; Abdel-Mottaleb, Mohamed

1997-01-01

This paper presents a novel approach for video retrieval from a large archive of MPEG or Motion JPEG compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the database for clips with similar contents. Video clips are characterized by a sequence of representative frame signatures, which are constructed from DC coefficients and motion information (`DC+M' signatures). The similarity between two video clips is determined by using their respective signatures. This method facilitates retrieval of clips for the purpose of video editing, broadcast news retrieval, or copyright violation detection.

Visual analytics for semantic queries of TerraSAR-X image content

Science.gov (United States)

Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

2015-10-01

With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain

Retrieval-Based Learning: Positive Effects of Retrieval Practice in Elementary School Children

Directory of Open Access Journals (Sweden)

Jeffrey D. Karpicke

2016-03-01

Full Text Available A wealth of research has demonstrated that practicing retrieval is a powerful way to enhance learning. However, nearly all prior research has examined retrieval practice with college students. Little is known about retrieval practice in children, and even less is known about possible individual differences in retrieval practice. In three experiments, 88 children (mean age 10 years studied a list of words and either restudied the items or practiced retrieving them. They then took a final free recall test (Experiments 1 and 2 or recognition test (Experiment 3. In all experiments, children showed robust retrieval practice effects. Although a range of individual differences in reading comprehension and processing speed were observed among these children, the benefits of retrieval practice were independent of these factors. The results contribute to the growing body of research supporting the mnemonic benefits of retrieval practice and provide preliminary evidence that practicing retrieval may be an effective learning strategy for children with varying levels of reading comprehension and processing speed.

Retrieving high-resolution images over the Internet from an anatomical image database

Science.gov (United States)

Strupp-Adams, Annette; Henderson, Earl

1999-12-01

The Visible Human Data set is an important contribution to the national collection of anatomical images. To enhance the availability of these images, the National Library of Medicine has supported the design and development of a prototype object-oriented image database which imports, stores, and distributes high resolution anatomical images in both pixel and voxel formats. One of the key database modules is its client-server Internet interface. This Web interface provides a query engine with retrieval access to high-resolution anatomical images that range in size from 100KB for browser viewable rendered images, to 1GB for anatomical structures in voxel file formats. The Web query and retrieval client-server system is composed of applet GUIs, servlets, and RMI application modules which communicate with each other to allow users to query for specific anatomical structures, and retrieve image data as well as associated anatomical images from the database. Selected images can be downloaded individually as single files via HTTP or downloaded in batch-mode over the Internet to the user's machine through an applet that uses Netscape's Object Signing mechanism. The image database uses ObjectDesign's object-oriented DBMS, ObjectStore that has a Java interface. The query and retrieval systems has been tested with a Java-CDE window system, and on the x86 architecture using Windows NT 4.0. This paper describes the Java applet client search engine that queries the database; the Java client module that enables users to view anatomical images online; the Java application server interface to the database which organizes data returned to the user, and its distribution engine that allow users to download image files individually and/or in batch-mode.

Query deforestation

OpenAIRE

Grust, Torsten; Scholl, Marc H.

1998-01-01

The construction of a declarative query engine for a DBMS includes the challenge of compiling algebraic queries into efficient execution plans that can be run on top of the persistent storage. This work pursues the goal of employing foldr-build deforestation for the derivation of efficient streaming programs - programs that do not allocate intermediate data structures to perform their task - from algebraic (combinator) query plans. The query engine is based on the insertion representation of ...

Design and development of a content-based medical image retrieval system for spine vertebrae irregularity.

Science.gov (United States)

Mustapha, Aouache; Hussain, Aini; Samad, Salina Abdul; Zulkifley, Mohd Asyraf; Diyana Wan Zaki, Wan Mimi; Hamid, Hamzaini Abdul

2015-01-16

Content-based medical image retrieval (CBMIR) system enables medical practitioners to perform fast diagnosis through quantitative assessment of the visual information of various modalities. In this paper, a more robust CBMIR system that deals with both cervical and lumbar vertebrae irregularity is afforded. It comprises three main phases, namely modelling, indexing and retrieval of the vertebrae image. The main tasks in the modelling phase are to improve and enhance the visibility of the x-ray image for better segmentation results using active shape model (ASM). The segmented vertebral fractures are then characterized in the indexing phase using region-based fracture characterization (RB-FC) and contour-based fracture characterization (CB-FC). Upon a query, the characterized features are compared to the query image. Effectiveness of the retrieval phase is determined by its retrieval, thus, we propose an integration of the predictor model based cross validation neural network (PMCVNN) and similarity matching (SM) in this stage. The PMCVNN task is to identify the correct vertebral irregularity class through classification allowing the SM process to be more efficient. Retrieval performance between the proposed and the standard retrieval architectures are then compared using retrieval precision (Pr@M) and average group score (AGS) measures. Experimental results show that the new integrated retrieval architecture performs better than those of the standard CBMIR architecture with retrieval results of cervical (AGS > 87%) and lumbar (AGS > 82%) datasets. The proposed CBMIR architecture shows encouraging results with high Pr@M accuracy. As a result, images from the same visualization class are returned for further used by the medical personnel.

Seasonal trends in sleep-disordered breathing: evidence from Internet search engine query data.

Science.gov (United States)

Ingram, David G; Matthews, Camilla K; Plante, David T

2015-03-01

The primary aim of the current study was to test the hypothesis that there is a seasonal component to snoring and obstructive sleep apnea (OSA) through the use of Google search engine query data. Internet search engine query data were retrieved from Google Trends from January 2006 to December 2012. Monthly normalized search volume was obtained over that 7-year period in the USA and Australia for the following search terms: "snoring" and "sleep apnea". Seasonal effects were investigated by fitting cosinor regression models. In addition, the search terms "snoring children" and "sleep apnea children" were evaluated to examine seasonal effects in pediatric populations. Statistically significant seasonal effects were found using cosinor analysis in both USA and Australia for "snoring" (p search term in Australia (p = 0.13). Seasonal patterns for "snoring children" and "sleep apnea children" were observed in the USA (p = 0.002 and p search volume to examine these search terms in Australia. All searches peaked in the winter or early spring in both countries, with the magnitude of seasonal effect ranging from 5 to 50 %. Our findings indicate that there are significant seasonal trends for both snoring and sleep apnea internet search engine queries, with a peak in the winter and early spring. Further research is indicated to determine the mechanisms underlying these findings, whether they have clinical impact, and if they are associated with other comorbid medical conditions that have similar patterns of seasonal exacerbation.

Mapping queries to the Linking Open Data cloud: a case study using DBpedia

NARCIS (Netherlands)

Meij, E.; Bron, M.; Hollink, L.; Huurnink, B.; de Rijke, M.

2011-01-01

We introduce the task of mapping search engine queries to DBpedia, a major linking hub in the Linking Open Data cloud. We propose and compare various methods for addressing this task, using a mixture of information retrieval and machine learning techniques. Specifically, we present a supervised

Spatial Search Techniques for Mobile 3D Queries in Sensor Web Environments

Directory of Open Access Journals (Sweden)

James D. Carswell

2013-03-01

Full Text Available Developing mobile geo-information systems for sensor web applications involves technologies that can access linked geographical and semantically related Internet information. Additionally, in tomorrow’s Web 4.0 world, it is envisioned that trillions of inexpensive micro-sensors placed throughout the environment will also become available for discovery based on their unique geo-referenced IP address. Exploring these enormous volumes of disparate heterogeneous data on today’s location and orientation aware smartphones requires context-aware smart applications and services that can deal with “information overload”. 3DQ (Three Dimensional Query is our novel mobile spatial interaction (MSI prototype that acts as a next-generation base for human interaction within such geospatial sensor web environments/urban landscapes. It filters information using “Hidden Query Removal” functionality that intelligently refines the search space by calculating the geometry of a three dimensional visibility shape (Vista space at a user’s current location. This 3D shape then becomes the query “window” in a spatial database for retrieving information on only those objects visible within a user’s actual 3D field-of-view. 3DQ reduces information overload and serves to heighten situation awareness on constrained commercial off-the-shelf devices by providing visibility space searching as a mobile web service. The effects of variations in mobile spatial search techniques in terms of query speed vs. accuracy are evaluated and presented in this paper.

3D Model Retrieval Based on Vector Quantisation Index Histograms

International Nuclear Information System (INIS)

Lu, Z M; Luo, H; Pan, J S

2006-01-01

This paper proposes a novel technique to retrieval 3D mesh models using vector quantisation index histograms. Firstly, points are sampled uniformly on mesh surface. Secondly, to a point five features representing global and local properties are extracted. Thus feature vectors of points are obtained. Third, we select several models from each class, and employ their feature vectors as a training set. After training using LBG algorithm, a public codebook is constructed. Next, codeword index histograms of the query model and those in database are computed. The last step is to compute the distance between histograms of the query and those of the models in database. Experimental results show the effectiveness of our method

Content Based Retrieval Database Management System with Support for Similarity Searching and Query Refinement

National Research Council Canada - National Science Library

Ortega-Binderberger, Michael

2002-01-01

... as a critical area of research. This thesis explores how to enhance database systems with content based search over arbitrary abstract data types in a similarity based framework with query refinement...

Learning Object Retrieval and Aggregation Based on Learning Styles

Science.gov (United States)

Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

2017-01-01

The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

Social media based NPL system to find and retrieve ARM data: Concept paper

Energy Technology Data Exchange (ETDEWEB)

Devarakonda, Ranjeet [ORNL; Giansiracusa, Michael T. [ORNL; Kumar, Jitendra [ORNL; Shanafield, III, Harold A. [ORNL

2017-12-01

Information connectivity and retrieval has a role in our daily lives. The most pervasive source of online information is databases. The amount of data is growing at rapid rate and database technology is improving and having a profound effect. Almost all online applications are storing and retrieving information from databases. One challenge in supplying the public with wider access to informational databases is the need for knowledge of database languages like Structured Query Language (SQL). Although the SQL language has been published in many forms, not everybody is able to write SQL queries. Another challenge is that it may not be practical to make the public aware of the structure of the database. There is a need for novice users to query relational databases using their natural language. To solve this problem, many natural language interfaces to structured databases have been developed. The goal is to provide more intuitive method for generating database queries and delivering responses. Social media makes it possible to interact with a wide section of the population. Through this medium, and with the help of Natural Language Processing (NLP) we can make the data of the Atmospheric Radiation Measurement Data Center (ADC) more accessible to the public. We propose an architecture for using Apache Lucene/Solr [1], OpenML [2,3], and Kafka [4] to generate an automated query/response system with inputs from Twitter5, our Cassandra DB, and our log database. Using the Twitter API and NLP we can give the public the ability to ask questions of our database and get automated responses.

Social media based NPL system to find and retrieve ARM data: Concept paper

Energy Technology Data Exchange (ETDEWEB)

Devarakonda, Ranjeet [ORNL; Giansiracusa, Michael T. [ORNL; Kumar, Jitendra [ORNL; Shanafield, III, Harold A. [ORNL

2018-01-01

Information connectivity and retrieval has a role in our daily lives. The most pervasive source of online information is databases. The amount of data is growing at rapid rate and database technology is improving and having a profound effect. Almost all online applications are storing and retrieving information from databases. One challenge in supplying the public with wider access to informational databases is the need for knowledge of database languages like Structured Query Language (SQL). Although the SQL language has been published in many forms, not everybody is able to write SQL queries. Another challenge is that it may not be practical to make the public aware of the structure of the database. There is a need for novice users to query relational databases using their natural language. To solve this problem, many natural language interfaces to structured databases have been developed. The goal is to provide more intuitive method for generating database queries and delivering responses. Social media makes it possible to interact with a wide section of the population. Through this medium, and with the help of Natural Language Processing (NLP) we can make the data of the Atmospheric Radiation Measurement Data Center (ADC) more accessible to the public. We propose an architecture for using Apache Lucene/Solr [1], OpenML [2,3], and Kafka [4] to generate an automated query/response system with inputs from Twitter5, our Cassandra DB, and our log database. Using the Twitter API and NLP we can give the public the ability to ask questions of our database and get automated responses.

A unified framework for image retrieval using keyword and visual features.

Science.gov (United States)

Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo

2005-07-01

In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.

Experiments with Cross-Language Information Retrieval on a Health Portal for Psychology and Psychotherapy.

Science.gov (United States)

Andrenucci, Andrea

2016-01-01

Few studies have been performed within cross-language information retrieval (CLIR) in the field of psychology and psychotherapy. The aim of this paper is to to analyze and assess the quality of available query translation methods for CLIR on a health portal for psychology. A test base of 100 user queries, 50 Multi Word Units (WUs) and 50 Single WUs, was used. Swedish was the source language and English the target language. Query translation methods based on machine translation (MT) and dictionary look-up were utilized in order to submit query translations to two search engines: Google Site Search and Quick Ask. Standard IR evaluation measures and a qualitative analysis were utilized to assess the results. The lexicon extracted with word alignment of the portal's parallel corpus provided better statistical results among dictionary look-ups. Google Translate provided more linguistically correct translations overall and also delivered better retrieval results in MT.

A Bayesian Approach to Interactive Retrieval

Science.gov (United States)

Tague, Jean M.

1973-01-01

A probabilistic model for interactive retrieval is presented. Bayesian statistical decision theory principles are applied: use of prior and sample information about the relationship of document descriptions to query relevance; maximization of expected value of a utility function, to the problem of optimally restructuring search strategies in an…

A Framework for WWW Query Processing

Science.gov (United States)

Wu, Binghui Helen; Wharton, Stephen (Technical Monitor)

2000-01-01

Query processing is the most common operation in a DBMS. Sophisticated query processing has been mainly targeted at a single enterprise environment providing centralized control over data and metadata. Submitting queries by anonymous users on the web is different in such a way that load balancing or DBMS' accessing control becomes the key issue. This paper provides a solution by introducing a framework for WWW query processing. The success of this framework lies in the utilization of query optimization techniques and the ontological approach. This methodology has proved to be cost effective at the NASA Goddard Space Flight Center Distributed Active Archive Center (GDAAC).

Semantic association ranking schemes for information retrieval ...

Indian Academy of Sciences (India)

retrieval applications using term association graph representation ... Department of Computer Science and Engineering, Government College of ... Introduction ... leads to poor precision, e.g., model, python, and chip. ...... The approaches proposed in this paper focuses on the query-centric re-ranking of search results.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring.

Science.gov (United States)

Alirezaie, Marjan; Kiselev, Andrey; Längkvist, Martin; Klügl, Franziska; Loutfi, Amy

2017-11-05

This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment-central Stockholm-in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as "find all regions close to schools and far from the flooded area". The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

An Ontology-Based Reasoning Framework for Querying Satellite Images for Disaster Monitoring

Directory of Open Access Journals (Sweden)

Marjan Alirezaie

2017-11-01

Full Text Available This paper presents a framework in which satellite images are classified and augmented with additional semantic information to enable queries about what can be found on the map at a particular location, but also about paths that can be taken. This is achieved by a reasoning framework based on qualitative spatial reasoning that is able to find answers to high level queries that may vary on the current situation. This framework called SemCityMap, provides the full pipeline from enriching the raw image data with rudimentary labels to the integration of a knowledge representation and reasoning methods to user interfaces for high level querying. To illustrate the utility of SemCityMap in a disaster scenario, we use an urban environment—central Stockholm—in combination with a flood simulation. We show that the system provides useful answers to high-level queries also with respect to the current flood status. Examples of such queries concern path planning for vehicles or retrieval of safe regions such as “find all regions close to schools and far from the flooded area”. The particular advantage of our approach lies in the fact that ontological information and reasoning is explicitly integrated so that queries can be formulated in a natural way using concepts on appropriate level of abstraction, including additional constraints.

A probabilistic justification for using tf.idf term weighting in information retrieval

NARCIS (Netherlands)

Hiemstra, Djoerd

2000-01-01

This paper presents a new probabilistic model of information retrieval. The most important modeling assumption made is that documents and queries are defined by an ordered sequence of single terms. This assumption is not made in well known existing models of information retrieval, but is essential

Semantics-Based Intelligent Indexing and Retrieval of Digital Images - A Case Study

Science.gov (United States)

Osman, Taha; Thakker, Dhavalkumar; Schaefer, Gerald

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they typically rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this chapter we present a semantically enabled image annotation and retrieval engine that is designed to satisfy the requirements of commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as presenting our initial thoughts on exploiting lexical databases for explicit semantic-based query expansion.

Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories

Science.gov (United States)

Tao, Shiqiang; Cui, Licong; Wu, Xi; Zhang, Guo-Qiang

2017-01-01

To help researchers better access clinical data, we developed a prototype query engine called DataSphere for exploring large-scale integrated clinical data repositories. DataSphere expedites data importing using a NoSQL data management system and dynamically renders its user interface for concept-based querying tasks. DataSphere provides an interactive query-building interface together with query translation and optimization strategies, which enable users to build and execute queries effectively and efficiently. We successfully loaded a dataset of one million patients for University of Kentucky (UK) Healthcare into DataSphere with more than 300 million clinical data records. We evaluated DataSphere by comparing it with an instance of i2b2 deployed at UK Healthcare, demonstrating that DataSphere provides enhanced user experience for both query building and execution. PMID:29854239

Facilitating Cohort Discovery by Enhancing Ontology Exploration, Query Management and Query Sharing for Large Clinical Data Repositories.

Science.gov (United States)

Tao, Shiqiang; Cui, Licong; Wu, Xi; Zhang, Guo-Qiang

2017-01-01

To help researchers better access clinical data, we developed a prototype query engine called DataSphere for exploring large-scale integrated clinical data repositories. DataSphere expedites data importing using a NoSQL data management system and dynamically renders its user interface for concept-based querying tasks. DataSphere provides an interactive query-building interface together with query translation and optimization strategies, which enable users to build and execute queries effectively and efficiently. We successfully loaded a dataset of one million patients for University of Kentucky (UK) Healthcare into DataSphere with more than 300 million clinical data records. We evaluated DataSphere by comparing it with an instance of i2b2 deployed at UK Healthcare, demonstrating that DataSphere provides enhanced user experience for both query building and execution.

Query-Biased Preview over Outsourced and Encrypted Data

Science.gov (United States)

Luo, Guangchun; Qin, Ke; Chen, Aiguo

2013-01-01

For both convenience and security, more and more users encrypt their sensitive data before outsourcing it to a third party such as cloud storage service. However, searching for the desired documents becomes problematic since it is costly to download and decrypt each possibly needed document to check if it contains the desired content. An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document. However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge. Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext) previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each document, the scheme has O(d) storage complexity and O(log(d/s) + s + d/s) communication complexity, where d is the document size and s is the snippet length. PMID:24078798

Query-biased preview over outsourced and encrypted data.

Science.gov (United States)

Peng, Ningduo; Luo, Guangchun; Qin, Ke; Chen, Aiguo

2013-01-01

For both convenience and security, more and more users encrypt their sensitive data before outsourcing it to a third party such as cloud storage service. However, searching for the desired documents becomes problematic since it is costly to download and decrypt each possibly needed document to check if it contains the desired content. An informative query-biased preview feature, as applied in modern search engine, could help the users to learn about the content without downloading the entire document. However, when the data are encrypted, securely extracting a keyword-in-context snippet from the data as a preview becomes a challenge. Based on private information retrieval protocol and the core concept of searchable encryption, we propose a single-server and two-round solution to securely obtain a query-biased snippet over the encrypted data from the server. We achieve this novel result by making a document (plaintext) previewable under any cryptosystem and constructing a secure index to support dynamic computation for a best matched snippet when queried by some keywords. For each document, the scheme has O(d) storage complexity and O(log(d/s) + s + d/s) communication complexity, where d is the document size and s is the snippet length.

Achieve Location Privacy-Preserving Range Query in Vehicular Sensing.

Science.gov (United States)

Kong, Qinglei; Lu, Rongxing; Ma, Maode; Bao, Haiyong

2017-08-08

Modern vehicles are equipped with a plethora of on-board sensors and large on-board storage, which enables them to gather and store various local-relevant data. However, the wide application of vehicular sensing has its own challenges, among which location-privacy preservation and data query accuracy are two critical problems. In this paper, we propose a novel range query scheme, which helps the data requester to accurately retrieve the sensed data from the distributive on-board storage in vehicular ad hoc networks (VANETs) with location privacy preservation. The proposed scheme exploits structured scalars to denote the locations of data requesters and vehicles, and achieves the privacy-preserving location matching with the homomorphic Paillier cryptosystem technique. Detailed security analysis shows that the proposed range query scheme can successfully preserve the location privacy of the involved data requesters and vehicles, and protect the confidentiality of the sensed data. In addition, performance evaluations are conducted to show the efficiency of the proposed scheme, in terms of computation delay and communication overhead. Specifically, the computation delay and communication overhead are not dependent on the length of the scalar, and they are only proportional to the number of vehicles.

Three-dimensional spatiotemporal features for fast content-based retrieval of focal liver lesions.

Science.gov (United States)

Roy, Sharmili; Chi, Yanling; Liu, Jimin; Venkatesh, Sudhakar K; Brown, Michael S

2014-11-01

Content-based image retrieval systems for 3-D medical datasets still largely rely on 2-D image-based features extracted from a few representative slices of the image stack. Most 2 -D features that are currently used in the literature not only model a 3-D tumor incompletely but are also highly expensive in terms of computation time, especially for high-resolution datasets. Radiologist-specified semantic labels are sometimes used along with image-based 2-D features to improve the retrieval performance. Since radiological labels show large interuser variability, are often unstructured, and require user interaction, their use as lesion characterizing features is highly subjective, tedious, and slow. In this paper, we propose a 3-D image-based spatiotemporal feature extraction framework for fast content-based retrieval of focal liver lesions. All the features are computer generated and are extracted from four-phase abdominal CT images. Retrieval performance and query processing times for the proposed framework is evaluated on a database of 44 hepatic lesions comprising of five pathological types. Bull's eye percentage score above 85% is achieved for three out of the five lesion pathologies and for 98% of query lesions, at least one same type of lesion is ranked among the top two retrieved results. Experiments show that the proposed system's query processing is more than 20 times faster than other already published systems that use 2-D features. With fast computation time and high retrieval accuracy, the proposed system has the potential to be used as an assistant to radiologists for routine hepatic tumor diagnosis.

Evaluation of information-theoretic similarity measures for content-based retrieval and detection of masses in mammograms

International Nuclear Information System (INIS)

Tourassi, Georgia D.; Harrawood, Brian; Singh, Swatee; Lo, Joseph Y.; Floyd, Carey E.

2007-01-01

The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrieval precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses

Secure Skyline Queries on Cloud Platform.

Science.gov (United States)

Liu, Jinfei; Yang, Juncheng; Xiong, Li; Pei, Jian

2017-04-01

Outsourcing data and computation to cloud server provides a cost-effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data (e.g., medical records) need to be protected from the cloud server and other unauthorized users. One approach is to outsource encrypted data to the cloud server and have the cloud server perform query processing on the encrypted data only. It remains a challenging task to support various queries over encrypted data in a secure and efficient way such that the cloud server does not gain any knowledge about the data, query, and query result. In this paper, we study the problem of secure skyline queries over encrypted data. The skyline query is particularly important for multi-criteria decision making but also presents significant challenges due to its complex computations. We propose a fully secure skyline query protocol on data encrypted using semantically-secure encryption. As a key subroutine, we present a new secure dominance protocol, which can be also used as a building block for other queries. Finally, we provide both serial and parallelized implementations and empirically study the protocols in terms of efficiency and scalability under different parameter settings, verifying the feasibility of our proposed solutions.

Biomedical information retrieval across languages.

Science.gov (United States)

Daumke, Philipp; Markü, Kornél; Poprat, Michael; Schulz, Stefan; Klar, Rüdiger

2007-06-01

This work presents a new dictionary-based approach to biomedical cross-language information retrieval (CLIR) that addresses many of the general and domain-specific challenges in current CLIR research. Our method is based on a multilingual lexicon that was generated partly manually and partly automatically, and currently covers six European languages. It contains morphologically meaningful word fragments, termed subwords. Using subwords instead of entire words significantly reduces the number of lexical entries necessary to sufficiently cover a specific language and domain. Mediation between queries and documents is based on these subwords as well as on lists of word-n-grams that are generated from large monolingual corpora and constitute possible translation units. The translations are then sent to a standard Internet search engine. This process makes our approach an effective tool for searching the biomedical content of the World Wide Web in different languages. We evaluate this approach using the OHSUMED corpus, a large medical document collection, within a cross-language retrieval setting.

Memory retrieval processes help explain the incumbency advantage

NARCIS (Netherlands)

Spälti, A.K.; Brandt, M.J.; Zeelenberg, M.

2017-01-01

Voters prefer political candidates who are currently in office (incumbents) over new candidates (challengers). Using the premise of query theory (Johnson, Häubl & Keinan, 2007), we clarify the underlying cognitive mechanisms by asking whether memory retrieval sequences affect political decision

Memory retrieval processes help explain the incumbency advantage

NARCIS (Netherlands)

Spälti, Anna Katharina; Brandt, Mark J.; Zeelenberg, Marcel

2017-01-01

Voters prefer political candidates who are currently in office (incumbents) over new candidates (challengers). Using the premise of query theory (Johnson, Häubl & Keinan, 2007), we clarify the underlying cognitive mechanisms by asking whether memory retrieval sequences affect political decision

Content-based image retrieval: Color-selection exploited

NARCIS (Netherlands)

Broek, E.L. van den; Vuurpijl, L.G.; Kisters, P. M. F.; Schmid, J.C.M. von; Moens, M.F.; Busser, R. de; Hiemstra, D.; Kraaij, W.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

Content-Based Image Retrieval: Color-selection exploited

NARCIS (Netherlands)

Moens, Marie-Francine; van den Broek, Egon; Vuurpijl, L.G.; de Brusser, Rik; Kisters, P.M.F.; Hiemstra, Djoerd; Kraaij, Wessel; von Schmid, J.C.M.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

G-Bean: an ontology-graph based web tool for biomedical literature retrieval.

Science.gov (United States)

Wang, James Z; Zhang, Yuanyuan; Dong, Liang; Li, Lin; Srimani, Pradip K; Yu, Philip S

2014-01-01

Currently, most people use NCBI's PubMed to search the MEDLINE database, an important bibliographical information source for life science and biomedical information. However, PubMed has some drawbacks that make it difficult to find relevant publications pertaining to users' individual intentions, especially for non-expert users. To ameliorate the disadvantages of PubMed, we developed G-Bean, a graph based biomedical search engine, to search biomedical articles in MEDLINE database more efficiently. G-Bean addresses PubMed's limitations with three innovations: (1) Parallel document index creation: a multithreaded index creation strategy is employed to generate the document index for G-Bean in parallel; (2) Ontology-graph based query expansion: an ontology graph is constructed by merging four major UMLS (Version 2013AA) vocabularies, MeSH, SNOMEDCT, CSP and AOD, to cover all concepts in National Library of Medicine (NLM) database; a Personalized PageRank algorithm is used to compute concept relevance in this ontology graph and the Term Frequency - Inverse Document Frequency (TF-IDF) weighting scheme is used to re-rank the concepts. The top 500 ranked concepts are selected for expanding the initial query to retrieve more accurate and relevant information; (3) Retrieval and re-ranking of documents based on user's search intention: after the user selects any article from the existing search results, G-Bean analyzes user's selections to determine his/her true search intention and then uses more relevant and more specific terms to retrieve additional related articles. The new articles are presented to the user in the order of their relevance to the already selected articles. Performance evaluation with 106 OHSUMED benchmark queries shows that G-Bean returns more relevant results than PubMed does when using these queries to search the MEDLINE database. PubMed could not even return any search result for some OHSUMED queries because it failed to form the appropriate Boolean

An hybrid method for the Arabic queries disambiguation to improve the relevance calculation in the IRS

OpenAIRE

Adil ENAANAI, Aziz SDIGUI DOUKKALI, El habib BENLAHMER

2012-01-01

In the information systems, the query’s expansion brings more benefices in the relevant documents extraction. However, the current expansion types are focused on the retrieve of the maximum of documents (reduce the silence). In Arabic, the queries are derived in many morphosemantical variants. Hence the diversity of the semantic interpretations that often creates a problem of ambiguity. Our objective is to prepare the Arabic request before its introduction to the document retrieval system. Th...

Improving information retrieval using Medical Subject Headings Concepts: a test case on rare and chronic diseases.

Science.gov (United States)

Darmoni, Stéfan J; Soualmia, Lina F; Letord, Catherine; Jaulent, Marie-Christine; Griffon, Nicolas; Thirion, Benoît; Névéol, Aurélie

2012-07-01

As more scientific work is published, it is important to improve access to the biomedical literature. Since 2000, when Medical Subject Headings (MeSH) Concepts were introduced, the MeSH Thesaurus has been concept based. Nevertheless, information retrieval is still performed at the MeSH Descriptor or Supplementary Concept level. The study assesses the benefit of using MeSH Concepts for indexing and information retrieval. Three sets of queries were built for thirty-two rare diseases and twenty-two chronic diseases: (1) using PubMed Automatic Term Mapping (ATM), (2) using Catalog and Index of French-language Health Internet (CISMeF) ATM, and (3) extrapolating the MEDLINE citations that should be indexed with a MeSH Concept. Type 3 queries retrieve significantly fewer results than type 1 or type 2 queries (about 18,000 citations versus 200,000 for rare diseases; about 300,000 citations versus 2,000,000 for chronic diseases). CISMeF ATM also provides better precision than PubMed ATM for both disease categories. Using MeSH Concept indexing instead of ATM is theoretically possible to improve retrieval performance with the current indexing policy. However, using MeSH Concept information retrieval and indexing rules would be a fundamentally better approach. These modifications have already been implemented in the CISMeF search engine.

Generating Concise Rules for Human Motion Retrieval

Science.gov (United States)

Mukai, Tomohiko; Wakisaka, Ken-Ichi; Kuriyama, Shigeru

This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.

An Index to All "Query" Computer Searches Completed from July 1973 to June 1974. Search Number 0403-0619. Information Series No. 24.

Science.gov (United States)

Wilder, Dolores J., Comp.; Hines, Rella, Comp.

The Tennessee Research Coordinating Unit (RCU) has implemented a computerized information retrieval system known as "Query," which allows for the retrieval of documents indexed in Research in Education (RIE), Current Index to Journals in Education (CIJE), and Abstracts of Instructional and Research Materials (AIM/ARM). The document…

Approximate dictionary queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Gasieniec, Leszek

1996-01-01

Given a set of n binary strings of length m each. We consider the problem of answering d-queries. Given a binary query string of length m, a d-query is to report if there exists a string in the set within Hamming distance d of . We present a data structure of size O(nm) supporting 1-queries in ti...

Hierarchical Fuzzy Feature Similarity Combination for Presentation Slide Retrieval

Directory of Open Access Journals (Sweden)

A. Kushki

2009-02-01

Full Text Available This paper proposes a novel XML-based system for retrieval of presentation slides to address the growing data mining needs in presentation archives for educational and scholarly settings. In particular, contextual information, such as structural and formatting features, is extracted from the open format XML representation of presentation slides. In response to a textual user query, each extracted feature is used to compute a fuzzy relevance score for each slide in the database. The fuzzy scores from the various features are then combined through a hierarchical scheme to generate a single relevance score per slide. Various fusion operators and their properties are examined with respect to their effect on retrieval performance. Experimental results indicate a significant increase in retrieval performance measured in terms of precision-recall. The improvements are attributed to both the incorporation of the contextual features and the hierarchical feature combination scheme.

An end user evaluation of query formulation and results review tools in three medical meta-search engines.

Science.gov (United States)

Leroy, Gondy; Xu, Jennifer; Chung, Wingyan; Eggers, Shauna; Chen, Hsinchun

2007-01-01

Retrieving sufficient relevant information online is difficult for many people because they use too few keywords to search and search engines do not provide many support tools. To further complicate the search, users often ignore support tools when available. Our goal is to evaluate in a realistic setting when users use support tools and how they perceive these tools. We compared three medical search engines with support tools that require more or less effort from users to form a query and evaluate results. We carried out an end user study with 23 users who were asked to find information, i.e., subtopics and supporting abstracts, for a given theme. We used a balanced within-subjects design and report on the effectiveness, efficiency and usability of the support tools from the end user perspective. We found significant differences in efficiency but did not find significant differences in effectiveness between the three search engines. Dynamic user support tools requiring less effort led to higher efficiency. Fewer searches were needed and more documents were found per search when both query reformulation and result review tools dynamically adjust to the user query. The query reformulation tool that provided a long list of keywords, dynamically adjusted to the user query, was used most often and led to more subtopics. As hypothesized, the dynamic result review tools were used more often and led to more subtopics than static ones. These results were corroborated by the usability questionnaires, which showed that support tools that dynamically optimize output were preferred.

A Query Cache Tool for Optimizing Repeatable and Parallel OLAP Queries

Science.gov (United States)

Santos, Ricardo Jorge; Bernardino, Jorge

On-line analytical processing against data warehouse databases is a common form of getting decision making information for almost every business field. Decision support information oftenly concerns periodic values based on regular attributes, such as sales amounts, percentages, most transactioned items, etc. This means that many similar OLAP instructions are periodically repeated, and simultaneously, between the several decision makers. Our Query Cache Tool takes advantage of previously executed queries, storing their results and the current state of the data which was accessed. Future queries only need to execute against the new data, inserted since the queries were last executed, and join these results with the previous ones. This makes query execution much faster, because we only need to process the most recent data. Our tool also minimizes the execution time and resource consumption for similar queries simultaneously executed by different users, putting the most recent ones on hold until the first finish and returns the results for all of them. The stored query results are held until they are considered outdated, then automatically erased. We present an experimental evaluation of our tool using a data warehouse based on a real-world business dataset and use a set of typical decision support queries to discuss the results, showing a very high gain in query execution time.

A Fast, Background-Independent Retrieval Strategy for Color Image Databases

National Research Council Canada - National Science Library

Das, M; Draper, B. A; Lim, W. J; Manmatha, R; Riseman, E. M

1996-01-01

We describe an interactive, multi-phase color-based image retrieval system which is capable of identifying query objects specified by the user in an image in the presence of significant, interfering backgrounds...

A LDA-based approach to promoting ranking diversity for genomics information retrieval.

Science.gov (United States)

Chen, Yan; Yin, Xiaoshi; Li, Zhoujun; Hu, Xiaohua; Huang, Jimmy Xiangji

2012-06-11

In the biomedical domain, there are immense data and tremendous increase of genomics and biomedical relevant publications. The wealth of information has led to an increasing amount of interest in and need for applying information retrieval techniques to access the scientific literature in genomics and related biomedical disciplines. In many cases, the desired information of a query asked by biologists is a list of a certain type of entities covering different aspects that are related to the question, such as cells, genes, diseases, proteins, mutations, etc. Hence, it is important of a biomedical IR system to be able to provide relevant and diverse answers to fulfill biologists' information needs. However traditional IR model only concerns with the relevance between retrieved documents and user query, but does not take redundancy between retrieved documents into account. This will lead to high redundancy and low diversity in the retrieval ranked lists. In this paper, we propose an approach which employs a topic generative model called Latent Dirichlet Allocation (LDA) to promoting ranking diversity for biomedical information retrieval. Different from other approaches or models which consider aspects on word level, our approach assumes that aspects should be identified by the topics of retrieved documents. We present LDA model to discover topic distribution of retrieval passages and word distribution of each topic dimension, and then re-rank retrieval results with topic distribution similarity between passages based on N-size slide window. We perform our approach on TREC 2007 Genomics collection and two distinctive IR baseline runs, which can achieve 8% improvement over the highest Aspect MAP reported in TREC 2007 Genomics track. The proposed method is the first study of adopting topic model to genomics information retrieval, and demonstrates its effectiveness in promoting ranking diversity as well as in improving relevance of ranked lists of genomics search

An On-Demand Retrieval Method Based on Hybrid NoSQL for Multi-Layer Image Tiles in Disaster Reduction Visualization

Directory of Open Access Journals (Sweden)

Linyao Qiu

2017-01-01

Full Text Available Monitoring, response, mitigation and damage assessment of disasters places a wide variety of demands on the spatial and temporal resolutions of remote sensing images. Images are divided into tile pyramids by data sources or resolutions and published as independent image services for visualization. A disaster-affected area is commonly covered by multiple image layers to express hierarchical surface information, which generates a large amount of namesake tiles from different layers that overlay the same location. The traditional tile retrieval method for visualization cannot distinguish between distinct layers and traverses all image datasets for each tile query. This process produces redundant queries and invalid access that can seriously affect the visualization performance of clients, servers and network transmission. This paper proposes an on-demand retrieval method for multi-layer images and defines semantic annotations to enrich the description of each dataset. By matching visualization demands with the semantic information of datasets, this method automatically filters inappropriate layers and finds the most suitable layer for the final tile query. The design and implementation are based on a two-layer NoSQL database architecture that provides scheduling optimization and concurrent processing capability. The experimental results reflect the effectiveness and stability of the approach for multi-layer retrieval in disaster reduction visualization.

A generative blog post retrieval model that uses query expansion based on external collections

NARCIS (Netherlands)

Weerkamp, W.; Balog, K.; de Rijke, M.; Su, K.-Y.; Su, J.; Wiebe, J.; Li, H.

2009-01-01

User generated content is characterized by short, noisy documents, with many spelling errors and unexpected language usage. To bridge the vocabulary gap between the user's information need and documents in a specific user generated content environment, the blogosphere, we apply a form of query

Query responses

Directory of Open Access Journals (Sweden)

Paweł Łupkowski

2017-05-01

Full Text Available In this article we consider the phenomenon of answering a query with a query. Although such answers are common, no large scale, corpus-based characterization exists, with the exception of clarification requests. After briefly reviewing different theoretical approaches on this subject, we present a corpus study of query responses in the British National Corpus and develop a taxonomy for query responses. We point at a variety of response categories that have not been formalized in previous dialogue work, particularly those relevant to adversarial interaction. We show that different response categories have significantly different rates of subsequent answer provision. We provide a formal analysis of the response categories in the framework of KoS.

A Fast, Background-Independent Retrieval Strategy for Color Image Databases

National Research Council Canada - National Science Library

Das, M; Draper, B. A; Lim, W. J; Manmatha, R; Riseman, E. M

1996-01-01

.... The method is fast and has low storage overhead. Good retrieval results are obtained with multi-colored query objects even when they occur in arbitrary sizes, rotations and locations in the database images...

The role of economics in the QUERI program: QUERI Series.

Science.gov (United States)

Smith, Mark W; Barnett, Paul G

2008-04-22

The United States (U.S.) Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) has implemented economic analyses in single-site and multi-site clinical trials. To date, no one has reviewed whether the QUERI Centers are taking an optimal approach to doing so. Consistent with the continuous learning culture of the QUERI Program, this paper provides such a reflection. We present a case study of QUERI as an example of how economic considerations can and should be integrated into implementation research within both single and multi-site studies. We review theoretical and applied cost research in implementation studies outside and within VA. We also present a critique of the use of economic research within the QUERI program. Economic evaluation is a key element of implementation research. QUERI has contributed many developments in the field of implementation but has only recently begun multi-site implementation trials across multiple regions within the national VA healthcare system. These trials are unusual in their emphasis on developing detailed costs of implementation, as well as in the use of business case analyses (budget impact analyses). Economics appears to play an important role in QUERI implementation studies, only after implementation has reached the stage of multi-site trials. Economic analysis could better inform the choice of which clinical best practices to implement and the choice of implementation interventions to employ. QUERI economics also would benefit from research on costing methods and development of widely accepted international standards for implementation economics.

Document retrieval on repetitive string collections.

Science.gov (United States)

Gagie, Travis; Hartikainen, Aleksi; Karhu, Kalle; Kärkkäinen, Juha; Navarro, Gonzalo; Puglisi, Simon J; Sirén, Jouni

2017-01-01

Most of the fastest-growing string collections today are repetitive, that is, most of the constituent documents are similar to many others. As these collections keep growing, a key approach to handling them is to exploit their repetitiveness, which can reduce their space usage by orders of magnitude. We study the problem of indexing repetitive string collections in order to perform efficient document retrieval operations on them. Document retrieval problems are routinely solved by search engines on large natural language collections, but the techniques are less developed on generic string collections. The case of repetitive string collections is even less understood, and there are very few existing solutions. We develop two novel ideas, interleaved LCPs and precomputed document lists , that yield highly compressed indexes solving the problem of document listing (find all the documents where a string appears), top- k document retrieval (find the k documents where a string appears most often), and document counting (count the number of documents where a string appears). We also show that a classical data structure supporting the latter query becomes highly compressible on repetitive data. Finally, we show how the tools we developed can be combined to solve ranked conjunctive and disjunctive multi-term queries under the simple [Formula: see text] model of relevance. We thoroughly evaluate the resulting techniques in various real-life repetitiveness scenarios, and recommend the best choices for each case.

Rare disease diagnosis as an information retrieval task

DEFF Research Database (Denmark)

Dragusin, Radu; Petcu, Paula; Lioma, Christina

2011-01-01

Increasingly more clinicians use web Information Retrieval (IR) systems to assist them in diagnosing difficult medical cases, for instance rare diseases that they may not be familiar with. However, web IR systems are not necessarily optimised for this task. For instance, clinicians’ queries tend...

Semantic Indexing and Retrieval based on Formal Concept Analysis

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Napoli , Amedeo

2012-01-01

Semantic indexing and retrieval has become an important research area, as the available amount of information on the Web is growing more and more. In this paper, we introduce an original approach to semantic indexing and retrieval based on Formal Concept Analysis. The concept lattice is used as a semantic index and we propose an original algorithm for traversing the lattice and answering user queries. This framework has been used and evaluated on song datasets.

A Two-Level Cache for Distributed Information Retrieval in Search Engines

Directory of Open Access Journals (Sweden)

Weizhe Zhang

2013-01-01

Full Text Available To improve the performance of distributed information retrieval in search engines, we propose a two-level cache structure based on the queries of the users’ logs. We extract the highest rank queries of users from the static cache, in which the queries are the most popular. We adopt the dynamic cache as an auxiliary to optimize the distribution of the cache data. We propose a distribution strategy of the cache data. The experiments prove that the hit rate, the efficiency, and the time consumption of the two-level cache have advantages compared with other structures of cache.

A two-level cache for distributed information retrieval in search engines.

Science.gov (United States)

Zhang, Weizhe; He, Hui; Ye, Jianwei

2013-01-01

To improve the performance of distributed information retrieval in search engines, we propose a two-level cache structure based on the queries of the users' logs. We extract the highest rank queries of users from the static cache, in which the queries are the most popular. We adopt the dynamic cache as an auxiliary to optimize the distribution of the cache data. We propose a distribution strategy of the cache data. The experiments prove that the hit rate, the efficiency, and the time consumption of the two-level cache have advantages compared with other structures of cache.

Retrieving self-vocalized information: An event-related potential (ERP) study on the effect of retrieval orientation.

Science.gov (United States)

Rosburg, Timm; Johansson, Mikael; Sprondel, Volker; Mecklinger, Axel

2014-11-18

Retrieval orientation refers to a pre-retrieval process and conceptualizes the specific form of processing that is applied to a retrieval cue. In the current event-related potential (ERP) study, we sought to find evidence for an involvement of the auditory cortex when subjects attempt to retrieve vocalized information, and hypothesized that adopting retrieval orientation would be beneficial for retrieval accuracy. During study, participants saw object words that they subsequently vocalized or visually imagined. At test, participants had to identify object names of one study condition as targets and to reject object names of the second condition together with new items. Target category switched after half of the test trials. Behaviorally, participants responded less accurately and more slowly to targets of the vocalize condition than to targets of the imagine condition. ERPs to new items varied at a single left electrode (T7) between 500 and 800ms, indicating a moderate retrieval orientation effect in the subject group as a whole. However, whereas the effect was strongly pronounced in participants with high retrieval accuracy, it was absent in participants with low retrieval accuracy. A current source density (CSD) mapping of the retrieval orientation effect indicated a source over left temporal regions. Independently from retrieval accuracy, the ERP retrieval orientation effect was surprisingly also modulated by test order. Findings are suggestive for an involvement of the auditory cortex in retrieval attempts of vocalized information and confirm that adopting retrieval orientation is potentially beneficial for retrieval accuracy. The effects of test order on retrieval-related processes might reflect a stronger focus on the newness of items in the more difficult test condition when participants started with this condition. Copyright © 2014 Elsevier Inc. All rights reserved.

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

Science.gov (United States)

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming

The role of economics in the QUERI program: QUERI Series

Directory of Open Access Journals (Sweden)

Smith Mark W

2008-04-01

Full Text Available Abstract Background The United States (U.S. Department of Veterans Affairs (VA Quality Enhancement Research Initiative (QUERI has implemented economic analyses in single-site and multi-site clinical trials. To date, no one has reviewed whether the QUERI Centers are taking an optimal approach to doing so. Consistent with the continuous learning culture of the QUERI Program, this paper provides such a reflection. Methods We present a case study of QUERI as an example of how economic considerations can and should be integrated into implementation research within both single and multi-site studies. We review theoretical and applied cost research in implementation studies outside and within VA. We also present a critique of the use of economic research within the QUERI program. Results Economic evaluation is a key element of implementation research. QUERI has contributed many developments in the field of implementation but has only recently begun multi-site implementation trials across multiple regions within the national VA healthcare system. These trials are unusual in their emphasis on developing detailed costs of implementation, as well as in the use of business case analyses (budget impact analyses. Conclusion Economics appears to play an important role in QUERI implementation studies, only after implementation has reached the stage of multi-site trials. Economic analysis could better inform the choice of which clinical best practices to implement and the choice of implementation interventions to employ. QUERI economics also would benefit from research on costing methods and development of widely accepted international standards for implementation economics.

Probabilistic Structured Query Methods

National Research Council Canada - National Science Library

Darwish, Kareem; Oard, Douglas W

2003-01-01

.... Statistically significant improvements in retrieval effectiveness are demonstrated for cross-language retrieval and for retrieval based on optical character recognition when replacement probabilities...

In-context query reformulation for failing SPARQL queries

Science.gov (United States)

Viswanathan, Amar; Michaelis, James R.; Cassidy, Taylor; de Mel, Geeth; Hendler, James

2017-05-01

Knowledge bases for decision support systems are growing increasingly complex, through continued advances in data ingest and management approaches. However, humans do not possess the cognitive capabilities to retain a bird's-eyeview of such knowledge bases, and may end up issuing unsatisfiable queries to such systems. This work focuses on the implementation of a query reformulation approach for graph-based knowledge bases, specifically designed to support the Resource Description Framework (RDF). The reformulation approach presented is instance-and schema-aware. Thus, in contrast to relaxation techniques found in the state-of-the-art, the presented approach produces in-context query reformulation.

Music Information Seeking Behaviour Poses Unique Challenges for the Design of Information Retrieval Systems. A Review of: Lee, J. H. (2010. Analysis of user needs and information features in natural language queries seeking music information. Journal of the American Society for information Science and Technology, 61, 1025-1045.

Directory of Open Access Journals (Sweden)

Cari Merkley

2010-12-01

Full Text Available Objective – To better understand music information seeking behaviour in a real life situation and to create a taxonomy relating to this behaviour to facilitate better comparison of music information retrieval studies in the future.Design – Content analysis of natural language queries.Setting – Google Answers, a fee based online service.Subjects – 1,705 queries and their related answers and comments posted in the music category of the Google Answers website before April 27, 2005.Methods – A total of 2,208 queries were retrieved from the music category on the Google Answers service. Google Answers was a fee based service in which users posted questions and indicated what they were willing to pay to have them answered. The queries selected for this study were posted prior to April 27, 2005, over a year before the service was discontinued completely. Of the 2208 queries taken from the site, only 1,705 were classified as relevant to the question of music information seeking by the researcher. The off-topic queries were not included in the study. Each of the 1,705 queries was coded according to the needs expressed by the user and the information provided to assist researchers in answering the question. The initial coding framework used by the researcher was informed by previous studies of music information retrieval to facilitate comparison, but was expanded and revised to reflect the evidence itself. Only the questions themselves were subjected to this iterative coding process. The answers provided by the Google Answer researchers and online comments posted by other users were examined by the author, but not coded for inclusion in the study.User needs in the questions were coded for their form and topic. Each question was assigned at least one form and one topic. Form refers to the type of question being asked and consisted of the following 10 categories: identification, location, verification, recommendation, evaluation, ready reference

Securing Document Warehouses against Brute Force Query Attacks

Directory of Open Access Journals (Sweden)

Sergey Vladimirovich Zapechnikov

2017-04-01

Full Text Available The paper presents the scheme of data management and protocols for securing document collection against adversary users who try to abuse their access rights to find out the full content of confidential documents. The configuration of secure document retrieval system is described and a suite of protocols among the clients, warehouse server, audit server and database management server is specified. The scheme makes it infeasible for clients to establish correspondence between the documents relevant to different search queries until a moderator won’t give access to these documents. The proposed solution allows ensuring higher security level for document warehouses.

Query optimization over crowdsourced data

KAUST Repository

Park, Hyunjung

2013-08-26

Deco is a comprehensive system for answering declarative queries posed over stored relational data together with data obtained on-demand from the crowd. In this paper we describe Deco\\'s cost-based query optimizer, building on Deco\\'s data model, query language, and query execution engine presented earlier. Deco\\'s objective in query optimization is to find the best query plan to answer a query, in terms of estimated monetary cost. Deco\\'s query semantics and plan execution strategies require several fundamental changes to traditional query optimization. Novel techniques incorporated into Deco\\'s query optimizer include a cost model distinguishing between "free" existing data versus paid new data, a cardinality estimation algorithm coping with changes to the database state during query execution, and a plan enumeration algorithm maximizing reuse of common subplans in a setting that makes reuse challenging. We experimentally evaluate Deco\\'s query optimizer, focusing on the accuracy of cost estimation and the efficiency of plan enumeration.

Using the fuzzy modeling for the retrieval algorithms

International Nuclear Information System (INIS)

Mohamed, A.H

2010-01-01

A rapid growth in number and size of images in databases and world wide web (www) has created a strong need for more efficient search and retrieval systems to exploit the benefits of this large amount of information. However, the collection of this information is now based on the image technology. One of the limitations of the current image analysis techniques necessitates that most image retrieval systems use some form of text description provided by the users as the basis to index and retrieve images. To overcome this problem, the proposed system introduces the using of fuzzy modeling to describe the image by using the linguistic ambiguities. Also, the proposed system can include vague or fuzzy terms in modeling the queries to match the image descriptions in the retrieval process. This can facilitate the indexing and retrieving process, increase their performance and decrease its computational time . Therefore, the proposed system can improve the performance of the traditional image retrieval algorithms.

Querying Business Process Models with VMQL

DEFF Research Database (Denmark)

Störrle, Harald; Acretoaie, Vlad

2013-01-01

The Visual Model Query Language (VMQL) has been invented with the objectives (1) to make it easier for modelers to query models effectively, and (2) to be universally applicable to all modeling languages. In previous work, we have applied VMQL to UML, and validated the first of these two claims. ...

A Novel Query Method for Spatial Data in Mobile Cloud Computing Environment

Directory of Open Access Journals (Sweden)

Guangsheng Chen

2018-01-01

Full Text Available With the development of network communication, a 1000-fold increase in traffic demand from 4G to 5G, it is critical to provide efficient and fast spatial data access interface for applications in mobile environment. In view of the low I/O efficiency and high latency of existing methods, this paper presents a memory-based spatial data query method that uses the distributed memory file system Alluxio to store data and build a two-level index based on the Alluxio key-value structure; moreover, it aims to solve the problem of low efficiency of traditional method; according to the characteristics of Spark computing framework, a data input format for spatial data query is proposed, which can selectively read the file data and reduce the data I/O. The comparative experiments show that the memory-based file system Alluxio has better I/O performance than the disk file system; compared with the traditional distributed query method, the method we proposed reduces the retrieval time greatly.

Semantic reasoning in zero example video event retrieval

NARCIS (Netherlands)

Boer, M.H.T. de; Lu, Y.J.; Zhang, H.; Schutte, K.; Ngo, C.W.; Kraaij, W.

2017-01-01

Searching in digital video data for high-level events, such as a parade or a car accident, is challenging when the query is textual and lacks visual example images or videos. Current research in deep neural networks is highly beneficial for the retrieval of high-level events using visual examples,

Querying on Federated Sensor Networks

Directory of Open Access Journals (Sweden)

Zuhal Can

2016-09-01

Full Text Available A Federated Sensor Network (FSN is a network of geographically distributed Wireless Sensor Networks (WSNs called islands. For querying on an FSN, we introduce the Layered Federated Sensor Network (L-FSN Protocol. For layered management, L-FSN provides communication among islands by its inter-island querying protocol by which a query packet routing path is determined according to some path selection policies. L-FSN allows autonomous management of each island by island-specific intra-island querying protocols that can be selected according to island properties. We evaluate the applicability of L-FSN and compare the L-FSN protocol with various querying protocols running on the flat federation model. Flat federation is a method to federate islands by running a single querying protocol on an entire FSN without distinguishing communication among and within islands. For flat federation, we select a querying protocol from geometrical, hierarchical cluster-based, hash-based, and tree-based WSN querying protocol categories. We found that a layered federation of islands by L-FSN increases the querying performance with respect to energy-efficiency, query resolving distance, and query resolving latency. Moreover, L-FSN’s flexibility of choosing intra-island querying protocols regarding the island size brings advantages on energy-efficiency and query resolving latency.

Evaluation of Term Ranking Algorithms for Pseudo-Relevance Feedback in MEDLINE Retrieval.

Science.gov (United States)

Yoo, Sooyoung; Choi, Jinwook

2011-06-01

The purpose of this study was to investigate the effects of query expansion algorithms for MEDLINE retrieval within a pseudo-relevance feedback framework. A number of query expansion algorithms were tested using various term ranking formulas, focusing on query expansion based on pseudo-relevance feedback. The OHSUMED test collection, which is a subset of the MEDLINE database, was used as a test corpus. Various ranking algorithms were tested in combination with different term re-weighting algorithms. Our comprehensive evaluation showed that the local context analysis ranking algorithm, when used in combination with one of the reweighting algorithms - Rocchio, the probabilistic model, and our variants - significantly outperformed other algorithm combinations by up to 12% (paired t-test; p algorithm pairs, at least in the context of the OHSUMED corpus. Comparative experiments on term ranking algorithms were performed in the context of a subset of MEDLINE documents. With medical documents, local context analysis, which uses co-occurrence with all query terms, significantly outperformed various term ranking methods based on both frequency and distribution analyses. Furthermore, the results of the experiments demonstrated that the term rank-based re-weighting method contributed to a remarkable improvement in mean average precision.

Combining semantic technologies with a content-based image retrieval system - Preliminary considerations

Science.gov (United States)

Chmiel, P.; Ganzha, M.; Jaworska, T.; Paprzycki, M.

2017-10-01

Nowadays, as a part of systematic growth of volume, and variety, of information that can be found on the Internet, we observe also dramatic increase in sizes of available image collections. There are many ways to help users browsing / selecting images of interest. One of popular approaches are Content-Based Image Retrieval (CBIR) systems, which allow users to search for images that match their interests, expressed in the form of images (query by example). However, we believe that image search and retrieval could take advantage of semantic technologies. We have decided to test this hypothesis. Specifically, on the basis of knowledge captured in the CBIR, we have developed a domain ontology of residential real estate (detached houses, in particular). This allows us to semantically represent each image (and its constitutive architectural elements) represented within the CBIR. The proposed ontology was extended to capture not only the elements resulting from image segmentation, but also "spatial relations" between them. As a result, a new approach to querying the image database (semantic querying) has materialized, thus extending capabilities of the developed system.

Utilizing Structural Knowledge for Information Retrieval in XML Databases

NARCIS (Netherlands)

Mihajlovic, V.; Hiemstra, Djoerd; Blok, H.E.; Apers, Peter M.G.

In this paper we address the problem of immediate translation of eXtensible Mark-up Language (XML) information retrieval (IR) queries to relational database expressions and stress the benefits of using an intermediate XML-specific algebra over relational algebra. We show how adding an XML-specific

A structural query system for Han characters

DEFF Research Database (Denmark)

Skala, Matthew

2016-01-01

The IDSgrep structural query system for Han character dictionaries is presented. This dictionary search system represents the spatial structure of Han characters using Extended Ideographic Description Sequences (EIDSes), a data model and syntax based on the Unicode IDS concept. It includes a query...... language for EIDS databases, with a freely available implementation and format translation from popular third-party IDS and XML character databases. The system is designed to suit the needs of font developers and foreign language learners. The search algorithm includes a bit vector index inspired by Bloom...... filters to support faster query operations. Experimental results are presented, evaluating the effect of the indexing on query performance....

Personalizing Information Retrieval Using Interaction Behaviors in Search Sessions in Different Types of Tasks

Science.gov (United States)

Liu, Chang

2012-01-01

When using information retrieval (IR) systems, users often pose short and ambiguous query terms. It is critical for IR systems to obtain more accurate representation of users' information need, their document preferences, and the context they are working in, and then incorporate them into the design of the systems to tailor retrieval to…

Improving Web Search for Difficult Queries

Science.gov (United States)

Wang, Xuanhui

2009-01-01

Search engines have now become essential tools in all aspects of our life. Although a variety of information needs can be served very successfully, there are still a lot of queries that search engines can not answer very effectively and these queries always make users feel frustrated. Since it is quite often that users encounter such "difficult…

LibKiSAO: a Java library for Querying KiSAO.

Science.gov (United States)

Zhukova, Anna; Adams, Richard; Laibe, Camille; Le Novère, Nicolas

2012-09-24

The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of Systems Biology models, their characteristics, parameters and inter-relationships. KiSAO enables the unambiguous identification of algorithms from simulation descriptions. Information about analogous methods having similar characteristics and about algorithm parameters incorporated into KiSAO is desirable for simulation tools. To retrieve this information programmatically an application programming interface (API) for KiSAO is needed. We developed libKiSAO, a Java library to enable querying of the KiSA Ontology. It implements methods to retrieve information about simulation algorithms stored in KiSAO, their characteristics and parameters, and methods to query the algorithm hierarchy and search for similar algorithms providing comparable results for the same simulation set-up. Using libKiSAO, simulation tools can make logical inferences based on this knowledge and choose the most appropriate algorithm to perform a simulation. LibKiSAO also enables simulation tools to handle a wider range of simulation descriptions by determining which of the available methods are similar and can be used instead of the one indicated in the simulation description if that one is not implemented. LibKiSAO enables Java applications to easily access information about simulation algorithms, their characteristics and parameters stored in the OWL-encoded Kinetic Simulation Algorithm Ontology. LibKiSAO can be used by simulation description editors and simulation tools to improve reproducibility of computational simulation tasks and facilitate model re-use.

Adaptation of machine translation for multilingual information retrieval in the medical domain.

Science.gov (United States)

Pecina, Pavel; Dušek, Ondřej; Goeuriot, Lorraine; Hajič, Jan; Hlaváčová, Jaroslava; Jones, Gareth J F; Kelly, Liadh; Leveling, Johannes; Mareček, David; Novák, Michal; Popel, Martin; Rosa, Rudolf; Tamchyna, Aleš; Urešová, Zdeňka

2014-07-01

We investigate machine translation (MT) of user search queries in the context of cross-lingual information retrieval (IR) in the medical domain. The main focus is on techniques to adapt MT to increase translation quality; however, we also explore MT adaptation to improve effectiveness of cross-lingual IR. Our MT system is Moses, a state-of-the-art phrase-based statistical machine translation system. The IR system is based on the BM25 retrieval model implemented in the Lucene search engine. The MT techniques employed in this work include in-domain training and tuning, intelligent training data selection, optimization of phrase table configuration, compound splitting, and exploiting synonyms as translation variants. The IR methods include morphological normalization and using multiple translation variants for query expansion. The experiments are performed and thoroughly evaluated on three language pairs: Czech-English, German-English, and French-English. MT quality is evaluated on data sets created within the Khresmoi project and IR effectiveness is tested on the CLEF eHealth 2013 data sets. The search query translation results achieved in our experiments are outstanding - our systems outperform not only our strong baselines, but also Google Translate and Microsoft Bing Translator in direct comparison carried out on all the language pairs. The baseline BLEU scores increased from 26.59 to 41.45 for Czech-English, from 23.03 to 40.82 for German-English, and from 32.67 to 40.82 for French-English. This is a 55% improvement on average. In terms of the IR performance on this particular test collection, a significant improvement over the baseline is achieved only for French-English. For Czech-English and German-English, the increased MT quality does not lead to better IR results. Most of the MT techniques employed in our experiments improve MT of medical search queries. Especially the intelligent training data selection proves to be very successful for domain adaptation of

Querying Workflow Logs

Directory of Open Access Journals (Sweden)

Yan Tang

2018-01-01

Full Text Available A business process or workflow is an assembly of tasks that accomplishes a business goal. Business process management is the study of the design, configuration/implementation, enactment and monitoring, analysis, and re-design of workflows. The traditional methodology for the re-design and improvement of workflows relies on the well-known sequence of extract, transform, and load (ETL, data/process warehousing, and online analytical processing (OLAP tools. In this paper, we study the ad hoc queryiny of process enactments for (data-centric business processes, bypassing the traditional methodology for more flexibility in querying. We develop an algebraic query language based on “incident patterns” with four operators inspired from Business Process Model and Notation (BPMN representation, allowing the user to formulate ad hoc queries directly over workflow logs. A formal semantics of this query language, a preliminary query evaluation algorithm, and a group of elementary properties of the operators are provided.

Data storage and retrieval for long-term dog studies

International Nuclear Information System (INIS)

Watson, C.R.; Trauger, G.M.; McIntyre, J.M.; Slavich, A.L.; Park, J.F.

1980-01-01

Over half of the 500,000 records collected on dogs in the last 20 years in our laboratory have been converted from sequential storage on magnetic tape to direct-access disk storage on a PDP 11/70 minicomputer. An interactive storage and retrieval system, based on a commercially available query language, has been developed to make these records more accessible. Data entry and retrieval are now performed by scientists and technicians rather than by keypunch operators and computer specialists. Further conversion awaits scheduled computer enhancement

Privacy-Aware Relevant Data Access with Semantically Enriched Search Queries for Untrusted Cloud Storage Services.

Science.gov (United States)

Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Lee, Sungyoung; Chung, Tae Choong

2016-01-01

Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud storage service can determine the presence or absence of a particular keyword by submitting search query in the form of a trapdoor. However, these trapdoor-based search queries are limited in functionality and cannot be used to identify secure outsourced data which contains semantically equivalent information. In addition, trapdoor-based methodologies are confined to pre-defined trapdoors and prevent subscribers from searching outsourced data with arbitrarily defined search criteria. To solve the problem of relevant data access, we have proposed an index-based privacy-aware search methodology that ensures semantic retrieval of data from an untrusted domain. This method ensures oblivious execution of a search query and leverages authorized subscribers to model conjunctive search queries without relying on predefined trapdoors. A security analysis of our proposed methodology shows that, in a conspired attack, unauthorized subscribers and untrusted cloud service providers cannot deduce any information that can lead to the potential loss of data privacy. A computational time analysis on commodity hardware demonstrates that our proposed methodology requires moderate computational resources to model a privacy-aware search query and for its oblivious evaluation on a cloud service provider.

Querying archetype-based EHRs by search ontology-based XPath engineering.

Science.gov (United States)

Kropf, Stefan; Uciteli, Alexandr; Schierle, Katrin; Krücken, Peter; Denecke, Kerstin; Herre, Heinrich

2018-05-11

Legacy data and new structured data can be stored in a standardized format as XML-based EHRs on XML databases. Querying documents on these databases is crucial for answering research questions. Instead of using free text searches, that lead to false positive results, the precision can be increased by constraining the search to certain parts of documents. A search ontology-based specification of queries on XML documents defines search concepts and relates them to parts in the XML document structure. Such query specification method is practically introduced and evaluated by applying concrete research questions formulated in natural language on a data collection for information retrieval purposes. The search is performed by search ontology-based XPath engineering that reuses ontologies and XML-related W3C standards. The key result is that the specification of research questions can be supported by the usage of search ontology-based XPath engineering. A deeper recognition of entities and a semantic understanding of the content is necessary for a further improvement of precision and recall. Key limitation is that the application of the introduced process requires skills in ontology and software development. In future, the time consuming ontology development could be overcome by implementing a new clinical role: the clinical ontologist. The introduced Search Ontology XML extension connects Search Terms to certain parts in XML documents and enables an ontology-based definition of queries. Search ontology-based XPath engineering can support research question answering by the specification of complex XPath expressions without deep syntax knowledge about XPaths.

jQuery Pocket Reference

CERN Document Server

Flanagan, David

2010-01-01

"As someone who uses jQuery on a regular basis, it was surprising to discover how much of the library I'm not using. This book is indispensable for anyone who is serious about using jQuery for non-trivial applications."-- Raffaele Cecco, longtime developer of video games, including Cybernoid, Exolon, and Stormlord jQuery is the "write less, do more" JavaScript library. Its powerful features and ease of use have made it the most popular client-side JavaScript framework for the Web. This book is jQuery's trusty companion: the definitive "read less, learn more" guide to the library. jQuery P

jQuery UI cookbook

CERN Document Server

Boduch, Adam

2013-01-01

Filled with a practical collection of recipes, jQuery UI Cookbook is full of clear, step-by-step instructions that will help you harness the powerful UI framework in jQuery. Depending on your needs, you can dip in and out of the Cookbook and its recipes, or follow the book from start to finish.If you are a jQuery UI developer looking to improve your existing applications, extract ideas for your new application, or to better understand the overall widget architecture, then jQuery UI Cookbook is a must-have for you. The reader should at least have a rudimentary understanding of what jQuery UI is

Instant jQuery selectors

CERN Document Server

De Rosa, Aurelio

2013-01-01

Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. Instant jQuery Selectors follows a simple how-to format with recipes aimed at making you well versed with the wide range of selectors that jQuery has to offer through a myriad of examples.Instant jQuery Selectors is for web developers who want to delve into jQuery from its very starting point: selectors. Even if you're already familiar with the framework and its selectors, you could find several tips and tricks that you aren't aware of, especially about performance and how jQuery ac

BR-Explorer: A sound and complete FCA-based retrieval algorithm (Poster)

OpenAIRE

Messai , Nizar; Devignes , Marie-Dominique; Napoli , Amedeo; Smaïl-Tabbone , Malika

2006-01-01

In this paper we present BR-Explorer, a sound and complete biological data sources retrieval algorithm based on Formal Concept Analysis and domain ontologies. BR-Explorer addresses the problem of retrieving the relevant data sources for a given query. Initially, a formal context representing the relation between biological data sources and their metadata is provided and its corresponding concept lattice is built. Then BR-Explorer starts by generating the formal concept for the considered quer...

Information Retrieval and Graph Analysis Approaches for Book Recommendation

Directory of Open Access Journals (Sweden)

Chahinez Benkoussas

2015-01-01

Full Text Available A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

Information Retrieval and Graph Analysis Approaches for Book Recommendation.

Science.gov (United States)

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

SkyQuery - A Prototype Distributed Query and Cross-Matching Web Service for the Virtual Observatory

Science.gov (United States)

Thakar, A. R.; Budavari, T.; Malik, T.; Szalay, A. S.; Fekete, G.; Nieto-Santisteban, M.; Haridas, V.; Gray, J.

2002-12-01

We have developed a prototype distributed query and cross-matching service for the VO community, called SkyQuery, which is implemented with hierarchichal Web Services. SkyQuery enables astronomers to run combined queries on existing distributed heterogeneous astronomy archives. SkyQuery provides a simple, user-friendly interface to run distributed queries over the federation of registered astronomical archives in the VO. The SkyQuery client connects to the portal Web Service, which farms the query out to the individual archives, which are also Web Services called SkyNodes. The cross-matching algorithm is run recursively on each SkyNode. Each archive is a relational DBMS with a HTM index for fast spatial lookups. The results of the distributed query are returned as an XML DataSet that is automatically rendered by the client. SkyQuery also returns the image cutout corresponding to the query result. SkyQuery finds not only matches between the various catalogs, but also dropouts - objects that exist in some of the catalogs but not in others. This is often as important as finding matches. We demonstrate the utility of SkyQuery with a brown-dwarf search between SDSS and 2MASS, and a search for radio-quiet quasars in SDSS, 2MASS and FIRST. The importance of a service like SkyQuery for the worldwide astronomical community cannot be overstated: data on the same objects in various archives is mapped in different wavelength ranges and looks very different due to different errors, instrument sensitivities and other peculiarities of each archive. Our cross-matching algorithm preforms a fuzzy spatial join across multiple catalogs. This type of cross-matching is currently often done by eye, one object at a time. A static cross-identification table for a set of archives would become obsolete by the time it was built - the exponential growth of astronomical data means that a dynamic cross-identification mechanism like SkyQuery is the only viable option. SkyQuery was funded by a

jQuery for designers beginner's guide

CERN Document Server

MacLees, Natalie

2014-01-01

A step-by-step guide that spices up your web pages and designs them in the way you want using the most widely used JavaScript library, jQuery. The beginner-friendly and easy-to-understand approach of the book will help get to grips with jQuery in no time. If you know the fundamentals of HTML and CSS, and want to extend your knowledge by learning to use JavaScript, then this is just the book for you. jQuery makes JavaScript straightforward and approachable - you'll be surprised at how easy it can be to add animations and special effects to your beautifully designed pages.

Multimedia Information Retrieval

CERN Document Server

Rueger, Stefan

2009-01-01

At its very core multimedia information retrieval means the process of searching for and finding multimedia documents; the corresponding research field is concerned with building the best possible multimedia search engines. The intriguing bit here is that the query itself can be a multimedia excerpt: For example, when you walk around in an unknown place and stumble across an interesting landmark, would it not be great if you could just take a picture with your mobile phone and send it to a service that finds a similar picture in a database and tells you more about the building -- and about its

A Retrieval Optimized Surveillance Video Storage System for Campus Application Scenarios

Directory of Open Access Journals (Sweden)

Shengcheng Ma

2018-01-01

Full Text Available This paper investigates and analyzes the characteristics of video data and puts forward a campus surveillance video storage system with the university campus as the specific application environment. Aiming at the challenge that the content-based video retrieval response time is too long, the key-frame index subsystem is designed. The key frame of the video can reflect the main content of the video. Extracted from the video, key frames are associated with the metadata information to establish the storage index. The key-frame index is used in lookup operations while querying. This method can greatly reduce the amount of video data reading and effectively improves the query’s efficiency. From the above, we model the storage system by a stochastic Petri net (SPN and verify the promotion of query performance by quantitative analysis.

Using citation data to improve retrieval from MEDLINE.

Science.gov (United States)

Bernstam, Elmer V; Herskovic, Jorge R; Aphinyanaphongs, Yindalon; Aliferis, Constantin F; Sriram, Madurai G; Hersh, William R

2006-01-01

To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. The most effective strategies were simple citation count and PageRank, which on average identified over six important articles in the first 100 results compared to 0.85 for the best noncitation-based algorithm (p PageRank more than simple citation count. However, in spite of citation lag, citation-based algorithms remain more effective than noncitation-based algorithms. CONCLUSION Algorithms that have proved successful on the World Wide Web can be applied to biomedical information retrieval. Citation-based algorithms can help identify important articles within large sets of relevant results. Further studies are needed to determine whether citation-based algorithms can effectively meet actual user information needs.

Query by image example: The CANDID approach

Energy Technology Data Exchange (ETDEWEB)

Kelly, P.M.; Cannon, M. [Los Alamos National Lab., NM (United States). Computer Research and Applications Group; Hush, D.R. [Univ. of New Mexico, Albuquerque, NM (United States). Dept. of Electrical and Computer Engineering

1995-02-01

CANDID (Comparison Algorithm for Navigating Digital Image Databases) was developed to enable content-based retrieval of digital imagery from large databases using a query-by-example methodology. A user provides an example image to the system, and images in the database that are similar to that example are retrieved. The development of CANDID was inspired by the N-gram approach to document fingerprinting, where a ``global signature`` is computed for every document in a database and these signatures are compared to one another to determine the similarity between any two documents. CANDID computes a global signature for every image in a database, where the signature is derived from various image features such as localized texture, shape, or color information. A distance between probability density functions of feature vectors is then used to compare signatures. In this paper, the authors present CANDID and highlight two results from their current research: subtracting a ``background`` signature from every signature in a database in an attempt to improve system performance when using inner-product similarity measures, and visualizing the contribution of individual pixels in the matching process. These ideas are applicable to any histogram-based comparison technique.

KARL: A Knowledge-Assisted Retrieval Language. Presentation visuals. M.S. Thesis Final Report, 1 Jul. 1985 - 31 Dec. 1987

Science.gov (United States)

Dominick, Wayne D. (Editor); Triantafyllopoulos, Spiros

1985-01-01

A collection of presentation visuals associated with the companion report entitled KARL: A Knowledge-Assisted Retrieval Language, is presented. Information is given on data retrieval, natural language database front ends, generic design objectives, processing capababilities and the query processing cycle.

Learning semantic query suggestions

NARCIS (Netherlands)

Meij, E.; Bron, M.; Hollink, L.; Huurnink, B.; de Rijke, M.

2009-01-01

An important application of semantic web technology is recognizing human-defined concepts in text. Query transformation is a strategy often used in search engines to derive queries that are able to return more useful search results than the original query and most popular search engines provide

NEOview: Near Earth Object Data Discovery and Query

Science.gov (United States)

Tibbetts, M.; Elvis, M.; Galache, J. L.; Harbo, P.; McDowell, J. C.; Rudenko, M.; Van Stone, D.; Zografou, P.

2013-10-01

Missions to Near Earth Objects (NEOs) figure prominently in NASA's Flexible Path approach to human space exploration. NEOs offer insight into both the origins of the Solar System and of life, as well as a source of materials for future missions. With NEOview scientists can locate NEO datasets, explore metadata provided by the archives, and query or combine disparate NEO datasets in the search for NEO candidates for exploration. NEOview is a software system that illustrates how standards-based interfaces facilitate NEO data discovery and research. NEOview software follows a client-server architecture. The server is a configurable implementation of the International Virtual Observatory Alliance (IVOA) Table Access Protocol (TAP), a general interface for tabular data access, that can be deployed as a front end to existing NEO datasets. The TAP client, seleste, is a graphical interface that provides intuitive means of discovering NEO providers, exploring dataset metadata to identify fields of interest, and constructing queries to retrieve or combine data. It features a powerful, graphical query builder capable of easing the user's introduction to table searches. Through science use cases, NEOview demonstrates how potential targets for NEO rendezvous could be identified by combining data from complementary sources. Through deployment and operations, it has been shown that the software components are data independent and configurable to many different data servers. As such, NEOview's TAP server and seleste TAP client can be used to create a seamless environment for data discovery and exploration for tabular data in any astronomical archive.

Cortisol effects on autobiographic memory retrieval in PTSD: an analysis of word valence and time until retrieval.

Science.gov (United States)

Wingenfeld, Katja; Driessen, Martin; Schlosser, Nicole; Terfehr, Kirsten; Carvalho Fernando, Silvia; Wolf, Oliver Tobias

2013-09-01

In healthy participants, cortisol administration has been found to impair autobiographic memory retrieval. We recently reported that administration of 10 mg of hydrocortisone had enhancing effects on autobiographical memory retrieval, i.e. more specific memory retrieval, in patients with posttraumatic stress disorder (PTSD), while in healthy controls the impairing effects were replicated. We here report a re-analysis of these data with respect to cue-word valence and retrieval time. In a placebo-controlled cross-over study, 43 patients with PTSD and 43 age- and sex-matched healthy controls received either placebo or hydrocortisone orally before the autobiographical memory test was performed. We found that the effects of cortisol on memory retrieval depended on cue-word valence and group (significant interaction effects of drug by group and drug by valence by group). The enhancing effect of cortisol on memory retrieval in PTSD seemed to be relatively independent of cue-word valence, while in the control group the impairing effects of cortisol were only seen in response to neutral cue-words. The second result of the study was that in patients as well as in controls, cortisol administration led to faster memory retrieval compared to placebo. This was seen in response to positive and (to lesser extend) to neutral cue-words, but not in response to negative cue-words. Our findings illustrate that the opposing effects of cortisol on autobiographical memory retrieval in PTSD patients and controls are further modulated by the emotionality of the cue-words.

Indexing for summary queries

DEFF Research Database (Denmark)

Yi, Ke; Wang, Lu; Wei, Zhewei

2014-01-01

), of a particular attribute of these records. Aggregation queries are especially useful in business intelligence and data analysis applications where users are interested not in the actual records, but some statistics of them. They can also be executed much more efficiently than reporting queries, by embedding...... returned by reporting queries. In this article, we design indexing techniques that allow for extracting a statistical summary of all the records in the query. The summaries we support include frequent items, quantiles, and various sketches, all of which are of central importance in massive data analysis....... Our indexes require linear space and extract a summary with the optimal or near-optimal query cost. We illustrate the efficiency and usefulness of our designs through extensive experiments and a system demonstration....

Head First jQuery

CERN Document Server

Benedetti, Ryan

2011-01-01

Want to add more interactivity and polish to your websites? Discover how jQuery can help you build complex scripting functionality in just a few lines of code. With Head First jQuery, you'll quickly get up to speed on this amazing JavaScript library by learning how to navigate HTML documents while handling events, effects, callbacks, and animations. By the time you've completed the book, you'll be incorporating Ajax apps, working seamlessly with HTML and CSS, and handling data with PHP, MySQL and JSON. If you want to learn-and understand-how to create interactive web pages, unobtrusive scrip

The CMS DBS query language

International Nuclear Information System (INIS)

Kuznetsov, Valentin; Riley, Daniel; Afaq, Anzar; Sekhri, Vijay; Guo Yuyi; Lueking, Lee

2010-01-01

The CMS experiment has implemented a flexible and powerful system enabling users to find data within the CMS physics data catalog. The Dataset Bookkeeping Service (DBS) comprises a database and the services used to store and access metadata related to CMS physics data. To this, we have added a generalized query system in addition to the existing web and programmatic interfaces to the DBS. This query system is based on a query language that hides the complexity of the underlying database structure by discovering the join conditions between database tables. This provides a way of querying the system that is simple and straightforward for CMS data managers and physicists to use without requiring knowledge of the database tables or keys. The DBS Query Language uses the ANTLR tool to build the input query parser and tokenizer, followed by a query builder that uses a graph representation of the DBS schema to construct the SQL query sent to underlying database. We will describe the design of the query system, provide details of the language components and overview of how this component fits into the overall data discovery system architecture.

Evaluation of an automatic weighting in a Boolean retrieval system with thesaurus, 2

International Nuclear Information System (INIS)

Ebinuma, Yukio

1980-01-01

Ranking performances created by the weighting of search terms are manifested with the same search topics and data files as in the test for the weighting of index terms. Weighted looser queries evince favourable retrieval performances on an average, though these are slightly inferior to conventional man prepared medium and tighter queries. The weight generation sample taken from a data file for over two months can be applied roughly to weighting in another data file. Degrees of improvement in precision and loss in recall at each ranked score position in other weight applied outputs are estimated from rank-precision curves for some weight generation samples. This relevance ranking scheme results in a considerable benefit in most of retrievals but is inferior to the weighting of index terms in view of applicability and ranking performances. (author)

Mastering jQuery mobile

CERN Document Server

Lambert, Chip

2015-01-01

You've started down the path of jQuery Mobile, now begin mastering some of jQuery Mobile's higher level topics. Go beyond jQuery Mobile's documentation and master one of the hottest mobile technologies out there. Previous JavaScript and PHP experience can help you get the most out of this book.

CDAPubMed: a browser extension to retrieve EHR-based biomedical literature

Directory of Open Access Journals (Sweden)

Perez-Rey David

2012-04-01

Full Text Available Abstract Background Over the last few decades, the ever-increasing output of scientific publications has led to new challenges to keep up to date with the literature. In the biomedical area, this growth has introduced new requirements for professionals, e.g., physicians, who have to locate the exact papers that they need for their clinical and research work amongst a huge number of publications. Against this backdrop, novel information retrieval methods are even more necessary. While web search engines are widespread in many areas, facilitating access to all kinds of information, additional tools are required to automatically link information retrieved from these engines to specific biomedical applications. In the case of clinical environments, this also means considering aspects such as patient data security and confidentiality or structured contents, e.g., electronic health records (EHRs. In this scenario, we have developed a new tool to facilitate query building to retrieve scientific literature related to EHRs. Results We have developed CDAPubMed, an open-source web browser extension to integrate EHR features in biomedical literature retrieval approaches. Clinical users can use CDAPubMed to: (i load patient clinical documents, i.e., EHRs based on the Health Level 7-Clinical Document Architecture Standard (HL7-CDA, (ii identify relevant terms for scientific literature search in these documents, i.e., Medical Subject Headings (MeSH, automatically driven by the CDAPubMed configuration, which advanced users can optimize to adapt to each specific situation, and (iii generate and launch literature search queries to a major search engine, i.e., PubMed, to retrieve citations related to the EHR under examination. Conclusions CDAPubMed is a platform-independent tool designed to facilitate literature searching using keywords contained in specific EHRs. CDAPubMed is visually integrated, as an extension of a widespread web browser, within the standard

Enabling Incremental Query Re-Optimization.

Science.gov (United States)

Liu, Mengmeng; Ives, Zachary G; Loo, Boon Thau

2016-01-01

As declarative query processing techniques expand to the Web, data streams, network routers, and cloud platforms, there is an increasing need to re-plan execution in the presence of unanticipated performance changes. New runtime information may affect which query plan we prefer to run. Adaptive techniques require innovation both in terms of the algorithms used to estimate costs , and in terms of the search algorithm that finds the best plan. We investigate how to build a cost-based optimizer that recomputes the optimal plan incrementally given new cost information, much as a stream engine constantly updates its outputs given new data. Our implementation especially shows benefits for stream processing workloads. It lays the foundations upon which a variety of novel adaptive optimization algorithms can be built. We start by leveraging the recently proposed approach of formulating query plan enumeration as a set of recursive datalog queries ; we develop a variety of novel optimization approaches to ensure effective pruning in both static and incremental cases. We further show that the lessons learned in the declarative implementation can be equally applied to more traditional optimizer implementations.

CUFID-query: accurate network querying through random walk based network flow estimation.

Science.gov (United States)

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2017-12-28

Functional modules in biological networks consist of numerous biomolecules and their complicated interactions. Recent studies have shown that biomolecules in a functional module tend to have similar interaction patterns and that such modules are often conserved across biological networks of different species. As a result, such conserved functional modules can be identified through comparative analysis of biological networks. In this work, we propose a novel network querying algorithm based on the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) framework combined with an efficient seed-and-extension approach. The proposed algorithm, CUFID-query, can accurately detect conserved functional modules as small subnetworks in the target network that are expected to perform similar functions to the given query functional module. The CUFID framework was recently developed for probabilistic pairwise global comparison of biological networks, and it has been applied to pairwise global network alignment, where the framework was shown to yield accurate network alignment results. In the proposed CUFID-query algorithm, we adopt the CUFID framework and extend it for local network alignment, specifically to solve network querying problems. First, in the seed selection phase, the proposed method utilizes the CUFID framework to compare the query and the target networks and to predict the probabilistic node-to-node correspondence between the networks. Next, the algorithm selects and greedily extends the seed in the target network by iteratively adding nodes that have frequent interactions with other nodes in the seed network, in a way that the conductance of the extended network is maximally reduced. Finally, CUFID-query removes irrelevant nodes from the querying results based on the personalized PageRank vector for the induced network that includes the fully extended network and its neighboring nodes. Through extensive

jQuery cookbook

CERN Document Server

2010-01-01

jQuery simplifies building rich, interactive web frontends. Getting started with this JavaScript library is easy, but it can take years to fully realize its breadth and depth; this cookbook shortens the learning curve considerably. With these recipes, you'll learn patterns and practices from 19 leading developers who use jQuery for everything from integrating simple components into websites and applications to developing complex, high-performance user interfaces. Ideal for newcomers and JavaScript veterans alike, jQuery Cookbook starts with the basics and then moves to practical use cases w

User perspectives on query difficulty

DEFF Research Database (Denmark)

Lioma, Christina; Larsen, Birger; Schütze, Hinrich

2011-01-01

be difficult for the system to address? (2) Are users aware of specific features in their query (e.g., domain-specificity, vagueness) that may render their query difficult for an IR system to address? A study of 420 queries from a Web search engine query log that are pre-categorised as easy, medium, hard...

An intelligent framework for medical image retrieval using MDCT and multi SVM.

Science.gov (United States)

Balan, J A Alex Rajju; Rajan, S Edward

2014-01-01

Volumes of medical images are rapidly generated in medical field and to manage them effectively has become a great challenge. This paper studies the development of innovative medical image retrieval based on texture features and accuracy. The objective of the paper is to analyze the image retrieval based on diagnosis of healthcare management systems. This paper traces the development of innovative medical image retrieval to estimate both the image texture features and accuracy. The texture features of medical images are extracted using MDCT and multi SVM. Both the theoretical approach and the simulation results revealed interesting observations and they were corroborated using MDCT coefficients and SVM methodology. All attempts to extract the data about the image in response to the query has been computed successfully and perfect image retrieval performance has been obtained. Experimental results on a database of 100 trademark medical images show that an integrated texture feature representation results in 98% of the images being retrieved using MDCT and multi SVM. Thus we have studied a multiclassification technique based on SVM which is prior suitable for medical images. The results show the retrieval accuracy of 98%, 99% for different sets of medical images with respect to the class of image.

Creating a Dutch testbed to evaluate the retrieval from textual databases

NARCIS (Netherlands)

Hiemstra, Djoerd; van Leeuwen, David A.

This paper describes the first large-scale evaluation of information retrieval systems using Dutch documents and queries. We describe in detail the characteristics of the Dutch test data, which is part of the official CLEF multilingual texttual database, and give an overview of the experimental

A study on PubMed search tag usage pattern: association rule mining of a full-day PubMed query log.

Science.gov (United States)

Mosa, Abu Saleh Mohammad; Yoo, Illhoi

2013-01-09

The practice of evidence-based medicine requires efficient biomedical literature search such as PubMed/MEDLINE. Retrieval performance relies highly on the efficient use of search field tags. The purpose of this study was to analyze PubMed log data in order to understand the usage pattern of search tags by the end user in PubMed/MEDLINE search. A PubMed query log file was obtained from the National Library of Medicine containing anonymous user identification, timestamp, and query text. Inconsistent records were removed from the dataset and the search tags were extracted from the query texts. A total of 2,917,159 queries were selected for this study issued by a total of 613,061 users. The analysis of frequent co-occurrences and usage patterns of the search tags was conducted using an association mining algorithm. The percentage of search tag usage was low (11.38% of the total queries) and only 2.95% of queries contained two or more tags. Three out of four users used no search tag and about two-third of them issued less than four queries. Among the queries containing at least one tagged search term, the average number of search tags was almost half of the number of total search terms. Navigational search tags are more frequently used than informational search tags. While no strong association was observed between informational and navigational tags, six (out of 19) informational tags and six (out of 29) navigational tags showed strong associations in PubMed searches. The low percentage of search tag usage implies that PubMed/MEDLINE users do not utilize the features of PubMed/MEDLINE widely or they are not aware of such features or solely depend on the high recall focused query translation by the PubMed's Automatic Term Mapping. The users need further education and interactive search application for effective use of the search tags in order to fulfill their biomedical information needs from PubMed/MEDLINE.

Heuristic query optimization for query multiple table and multiple clausa on mobile finance application

Science.gov (United States)

Indrayana, I. N. E.; P, N. M. Wirasyanti D.; Sudiartha, I. KG

2018-01-01

Mobile application allow many users to access data from the application without being limited to space, space and time. Over time the data population of this application will increase. Data access time will cause problems if the data record has reached tens of thousands to millions of records.The objective of this research is to maintain the performance of data execution for large data records. One effort to maintain data access time performance is to apply query optimization method. The optimization used in this research is query heuristic optimization method. The built application is a mobile-based financial application using MySQL database with stored procedure therein. This application is used by more than one business entity in one database, thus enabling rapid data growth. In this stored procedure there is an optimized query using heuristic method. Query optimization is performed on a “Select” query that involves more than one table with multiple clausa. Evaluation is done by calculating the average access time using optimized and unoptimized queries. Access time calculation is also performed on the increase of population data in the database. The evaluation results shown the time of data execution with query heuristic optimization relatively faster than data execution time without using query optimization.

The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries

Directory of Open Access Journals (Sweden)

Apweiler Rolf

2006-02-01

Full Text Available Abstract Background With the vast amounts of biomedical data being generated by high-throughput analysis methods, controlled vocabularies and ontologies are becoming increasingly important to annotate units of information for ease of search and retrieval. Each scientific community tends to create its own locally available ontology. The interfaces to query these ontologies tend to vary from group to group. We saw the need for a centralized location to perform controlled vocabulary queries that would offer both a lightweight web-accessible user interface as well as a consistent, unified SOAP interface for automated queries. Results The Ontology Lookup Service (OLS was created to integrate publicly available biomedical ontologies into a single database. All modified ontologies are updated daily. A list of currently loaded ontologies is available online. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A programmatic interface is available to query the webservice using SOAP. The service is described by a WSDL descriptor file available online. A sample Java client to connect to the webservice using SOAP is available for download from SourceForge. All OLS source code is publicly available under the open source Apache Licence. Conclusion The OLS provides a user-friendly single entry point for publicly available ontologies in the Open Biomedical Ontology (OBO format. It can be accessed interactively or programmatically at http://www.ebi.ac.uk/ontology-lookup/.

Mastering jQuery

CERN Document Server

Libby, Alex

2015-01-01

If you are a developer who is already familiar with using jQuery and wants to push your skill set further, then this book is for you. The book assumes an intermediate knowledge level of jQuery, JavaScript, HTML5, and CSS.

Smart Query Answering for Marine Sensor Data

Directory of Open Access Journals (Sweden)

Paulo de Souza

2011-03-01

Full Text Available We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks.

Smart query answering for marine sensor data.

Science.gov (United States)

Shahriar, Md Sumon; de Souza, Paulo; Timms, Greg

2011-01-01

We review existing query answering systems for sensor data. We then propose an extended query answering approach termed smart query, specifically for marine sensor data. The smart query answering system integrates pattern queries and continuous queries. The proposed smart query system considers both streaming data and historical data from marine sensor networks. The smart query also uses query relaxation technique and semantics from domain knowledge as a recommender system. The proposed smart query benefits in building data and information systems for marine sensor networks.

Error Checking for Chinese Query by Mining Web Log

Directory of Open Access Journals (Sweden)

Jianyong Duan

2015-01-01

Full Text Available For the search engine, error-input query is a common phenomenon. This paper uses web log as the training set for the query error checking. Through the n-gram language model that is trained by web log, the queries are analyzed and checked. Some features including query words and their number are introduced into the model. At the same time data smoothing algorithm is used to solve data sparseness problem. It will improve the overall accuracy of the n-gram model. The experimental results show that it is effective.

Intelligent Information Retrieval: Diagnosing Information Need. Part I. The Theoretical Framework for Developing an Intelligent IR Tool.

Science.gov (United States)

Cole, Charles

1998-01-01

Suggests that the principles underlying the procedure used by doctors to diagnose a patient's disease are useful in the design of intelligent information-retrieval systems because the task of the doctor is conceptually similar to the computer or human intermediary's task in information retrieval: to draw out the user's query/information need.…

Encoding and Retrieval Processes Involved in the Access of Source Information in the Absence of Item Memory

Science.gov (United States)

Ball, B. Hunter; DeWitt, Michael R.; Knight, Justin B.; Hicks, Jason L.

2014-01-01

The current study sought to examine the relative contributions of encoding and retrieval processes in accessing contextual information in the absence of item memory using an extralist cuing procedure in which the retrieval cues used to query memory for contextual information were "related" to the target item but never actually studied.…

Three-Dimensional Model Retrieval Using Dynamic Multi-Descriptor Fusion

Institute of Scientific and Technical Information of China (English)

Jau-Ling Shi; Chang-Hsing Lee; Yao-Wen Hou; Po-Ting Yeh

2017-01-01

In this paper, we propose a dynamic multi-descriptor fusion (DMDF) approach to improving the retrieval accuracy of 3-dimensional (3D) model retrieval systems. First, an independent retrieval list is generated by using each individual descriptor. Second, we propose an automatic relevant/irrelevant models selection (ARMS) approach to selecting the relevant and irrelevant 3D models automatically without any user interaction. A weighted distance, in which the weight associated with each individual descriptor is learnt by using the selected relevant and irrelevant models, is used to measure the similarity between two 3D models. Furthermore, a descriptor-dependent adaptive query point movement (AQPM) approach is employed to update every feature vector. This set of new feature vectors is used to index 3D models in the next search process. Four 3D model databases are used to compare the retrieval accuracy of our proposed DMDF approach with several descriptors as well as some well-known information fusion methods. Experimental results have shown that our proposed DMDF approach provides a promising retrieval result and always yields the best retrieval accuracy.

Music Information Retrieval from a Singing Voice Using Lyrics and Melody Information

Directory of Open Access Journals (Sweden)

Shozo Makino

2007-01-01

Full Text Available Recently, several music information retrieval (MIR systems which retrieve musical pieces by the user's singing voice have been developed. All of these systems use only melody information for retrieval, although lyrics information is also useful for retrieval. In this paper, we propose a new MIR system that uses both lyrics and melody information. First, we propose a new lyrics recognition method. A finite state automaton (FSA is used as recognition grammar, and about 86% retrieval accuracy was obtained. We also develop an algorithm for verifying a hypothesis output by a lyrics recognizer. Melody information is extracted from an input song using several pieces of information of the hypothesis, and a total score is calculated from the recognition score and the verification score. From the experimental results, 95.0% retrieval accuracy was obtained with a query consisting of five words.

Music Information Retrieval from a Singing Voice Using Lyrics and Melody Information

Directory of Open Access Journals (Sweden)

Suzuki Motoyuki

2007-01-01

Full Text Available Recently, several music information retrieval (MIR systems which retrieve musical pieces by the user's singing voice have been developed. All of these systems use only melody information for retrieval, although lyrics information is also useful for retrieval. In this paper, we propose a new MIR system that uses both lyrics and melody information. First, we propose a new lyrics recognition method. A finite state automaton (FSA is used as recognition grammar, and about retrieval accuracy was obtained. We also develop an algorithm for verifying a hypothesis output by a lyrics recognizer. Melody information is extracted from an input song using several pieces of information of the hypothesis, and a total score is calculated from the recognition score and the verification score. From the experimental results, 95.0 retrieval accuracy was obtained with a query consisting of five words.

jQuery For Dummies

CERN Document Server

Beighley, Lynn

2010-01-01

Learn how jQuery can make your Web page or blog stand out from the crowd!. jQuery is free, open source software that allows you to extend and customize Joomla!, Drupal, AJAX, and WordPress via plug-ins. Assuming no previous programming experience, Lynn Beighley takes you through the basics of jQuery from the very start. You'll discover how the jQuery library separates itself from other JavaScript libraries through its ease of use, compactness, and friendliness if you're a beginner programmer. Written in the easy-to-understand style of the For Dummies brand, this book demonstrates how you can a

Web development with jQuery

CERN Document Server

York, Richard

2015-01-01

Newly revised and updated resource on jQuery's many features and advantages Web Development with jQuery offers a major update to the popular Beginning JavaScript and CSS Development with jQuery from 2009. More than half of the content is new or updated, and reflects recent innovations with regard to mobile applications, jQuery mobile, and the spectrum of associated plugins. Readers can expect thorough revisions with expanded coverage of events, CSS, AJAX, animation, and drag and drop. New chapters bring developers up to date on popular features like jQuery UI, navigation, tables, interacti

Optimizing Temporal Queries

DEFF Research Database (Denmark)

Toman, David; Bowman, Ivan Thomas

2003-01-01

Recent research in the area of temporal databases has proposed a number of query languages that vary in their expressive power and the semantics they provide to users. These query languages represent a spectrum of solutions to the tension between clean semantics and efficient evaluation. Often, t...

Using background knowledge for picture organization and retrieval

Science.gov (United States)

Quintana, Yuri

1997-01-01

A picture knowledge base management system is described that is used to represent, organize and retrieve pictures from a frame knowledge base. Experiments with human test subjects were conducted to obtain further descriptions of pictures from news magazines. These descriptions were used to represent the semantic content of pictures in frame representations. A conceptual clustering algorithm is described which organizes pictures not only on the observable features, but also on implicit properties derived from the frame representations. The algorithm uses inheritance reasoning to take into account background knowledge in the clustering. The algorithm creates clusters of pictures using a group similarity function that is based on the gestalt theory of picture perception. For each cluster created, a frame is generated which describes the semantic content of pictures in the cluster. Clustering and retrieval experiments were conducted with and without background knowledge. The paper shows how the use of background knowledge and semantic similarity heuristics improves the speed, precision, and recall of queries processed. The paper concludes with a discussion of how natural language processing of can be used to assist in the development of knowledge bases and the processing of user queries.

Keyword Query Expansion Paradigm Based on Recommendation and Interpretation in Relational Databases

Directory of Open Access Journals (Sweden)

Yingqi Wang

2017-01-01

Full Text Available Due to the ambiguity and impreciseness of keyword query in relational databases, the research on keyword query expansion has attracted wide attention. Existing query expansion methods expose users’ query intention to a certain extent, but most of them cannot balance the precision and recall. To address this problem, a novel two-step query expansion approach is proposed based on query recommendation and query interpretation. First, a probabilistic recommendation algorithm is put forward by constructing a term similarity matrix and Viterbi model. Second, by using the translation algorithm of triples and construction algorithm of query subgraphs, query keywords are translated to query subgraphs with structural and semantic information. Finally, experimental results on a real-world dataset demonstrate the effectiveness and rationality of the proposed method.

IMIRSEL: a secure music retrieval testing environment

Science.gov (United States)

Downie, John S.

2004-10-01

The Music Information Retrieval (MIR) and Music Digital Library (MDL) research communities have long noted the need for formal evaluation mechanisms. Issues concerning the unavailability of freely-available music materials have greatly hindered the creation of standardized test collections with which these communities could scientifically assess the strengths and weaknesses of their various music retrieval techniques. The International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) is being developed at the University of Illinois at Urbana-Champaign (UIUC) specifically to overcome this hindrance to the scientific evaluation of MIR/MDL systems. Together with its subsidiary Human Use of Music Information Retrieval Systems (HUMIRS) project, IMIRSEL will allow MIR/MDL researchers access to the standardized large-scale collection of copyright-sensitive music materials and standardized test queries being housed at UIUC's National Center for Supercomputing Applications (NCSA). Virtual Research Labs (VRL), based upon NCSA's Data-to-Knowledge (D2K) tool set, are being developed through which MIR/MDL researchers will interact with the music materials under a "trusted code" security model.

jQuery Mobile

CERN Document Server

Reid, Jon

2011-01-01

Native apps have distinct advantages, but the future belongs to mobile web apps that function on a broad range of smartphones and tablets. Get started with jQuery Mobile, the touch-optimized framework for creating apps that look and behave consistently across many devices. This concise book provides HTML5, CSS3, and JavaScript code examples, screen shots, and step-by-step guidance to help you build a complete working app with jQuery Mobile. If you're already familiar with the jQuery JavaScript library, you can use your existing skills to build cross-platform mobile web apps right now. This b

A Heuristic Hierarchical Scheme for Academic Search and Retrieval

DEFF Research Database (Denmark)

Amolochitis, Emmanouil; Christou, Ioannis T.; Tan, Zheng-Hua

2013-01-01

and a graph-theoretic computed score that relates the paper’s index terms with each other. We designed and developed a meta-search engine that submits user queries to standard digital repositories of academic publications and re-ranks the repository results using the hierarchical heuristic scheme. We evaluate......, and by more than 907.5% in terms of LEX. We also re-rank the top-10 results of a subset of the original 58 user queries produced by Google Scholar, Microsoft Academic Search, and ArnetMiner; the results show that PubSearch compares very well against these search engines as well. The proposed scheme can...... be easily plugged in any existing search engine for retrieval of academic publications....

Crossover Improvement for the Genetic Algorithm in Information Retrieval.

Science.gov (United States)

Vrajitoru, Dana

1998-01-01

In information retrieval (IR), the aim of genetic algorithms (GA) is to help a system to find, in a huge documents collection, a good reply to a query expressed by the user. Analysis of phenomena seen during the implementation of a GA for IR has led to a new crossover operation, which is introduced and compared to other learning methods.…

Lazy Toggle PRM: A single-query approach to motion planning

KAUST Repository

Denny, Jory

2013-05-01

Probabilistic RoadMaps (PRMs) are quite suc-cessful in solving complex and high-dimensional motion plan-ning problems. While particularly suited for multiple-query scenarios and expansive spaces, they lack efficiency in both solving single-query scenarios and mapping narrow spaces. Two PRM variants separately tackle these gaps. Lazy PRM reduces the computational cost of roadmap construction for single-query scenarios by delaying roadmap validation until query time. Toggle PRM is well suited for mapping narrow spaces by mapping both Cfree and Cobst, which gives certain theoretical benefits. However, fully validating the two resulting roadmaps can be costly. We present a strategy, Lazy Toggle PRM, for integrating these two approaches into a method which is both suited for narrow passages and efficient single-query calculations. This simultaneously addresses two challenges of PRMs. Like Lazy PRM, Lazy Toggle PRM delays validation of roadmaps until query time, but if no path is found, the algorithm augments the roadmap using the Toggle PRM methodology. We demonstrate the effectiveness of Lazy Toggle PRM in a wide range of scenarios, including those with narrow passages and high descriptive complexity (e.g., those described by many triangles), concluding that it is more effective than existing methods in solving difficult queries. © 2013 IEEE.

Query Health: standards-based, cross-platform population health surveillance.

Science.gov (United States)

Klann, Jeffrey G; Buck, Michael D; Brown, Jeffrey; Hadley, Marc; Elmore, Richard; Weber, Griffin M; Murphy, Shawn N

2014-01-01

Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level health queries across diverse clinical systems with disparate data models. Here we review Query Health activities, including a standards-based methodology, an open-source reference implementation, and three pilot projects. Query Health defined a standards-based approach for distributed population health queries, using an ontology based on the Quality Data Model and Consolidated Clinical Document Architecture, Health Quality Measures Format (HQMF) as the query language, the Query Envelope as the secure transport layer, and the Quality Reporting Document Architecture as the result language. We implemented this approach using Informatics for Integrating Biology and the Bedside (i2b2) and hQuery for data analytics and PopMedNet for access control, secure query distribution, and response. We deployed the reference implementation at three pilot sites: two public health departments (New York City and Massachusetts) and one pilot designed to support Food and Drug Administration post-market safety surveillance activities. The pilots were successful, although improved cross-platform data normalization is needed. This initiative resulted in a standards-based methodology for population health queries, a reference implementation, and revision of the HQMF standard. It also informed future directions regarding interoperability and data access for ONC's Data Access Framework initiative. Query Health was a test of the learning health system that supplied a functional methodology and reference implementation for distributed population health queries that has been validated at three sites. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under

Incremental Query Rewriting with Resolution

Science.gov (United States)

Riazanov, Alexandre; Aragão, Marcelo A. T.

We address the problem of semantic querying of relational databases (RDB) modulo knowledge bases using very expressive knowledge representation formalisms, such as full first-order logic or its various fragments. We propose to use a resolution-based first-order logic (FOL) reasoner for computing schematic answers to deductive queries, with the subsequent translation of these schematic answers to SQL queries which are evaluated using a conventional relational DBMS. We call our method incremental query rewriting, because an original semantic query is rewritten into a (potentially infinite) series of SQL queries. In this chapter, we outline the main idea of our technique - using abstractions of databases and constrained clauses for deriving schematic answers, and provide completeness and soundness proofs to justify the applicability of this technique to the case of resolution for FOL without equality. The proposed method can be directly used with regular RDBs, including legacy databases. Moreover, we propose it as a potential basis for an efficient Web-scale semantic search technology.

Range-clustering queries

NARCIS (Netherlands)

Abrahamsen, M.; de Berg, M.T.; Buchin, K.A.; Mehr, M.; Mehrabi, A.D.

2017-01-01

In a geometric k -clustering problem the goal is to partition a set of points in R d into k subsets such that a certain cost function of the clustering is minimized. We present data structures for orthogonal range-clustering queries on a point set S : given a query box Q and an integer k>2 , compute

Elsevier’s approach to the bioCADDIE 2016 Dataset Retrieval Challenge

Science.gov (United States)

Scerri, Antony; Kuriakose, John; Deshmane, Amit Ajit; Stanger, Mark; Moore, Rebekah; Naik, Raj; de Waard, Anita

2017-01-01

Abstract We developed a two-stream, Apache Solr-based information retrieval system in response to the bioCADDIE 2016 Dataset Retrieval Challenge. One stream was based on the principle of word embeddings, the other was rooted in ontology based indexing. Despite encountering several issues in the data, the evaluation procedure and the technologies used, the system performed quite well. We provide some pointers towards future work: in particular, we suggest that more work in query expansion could benefit future biomedical search engines. Database URL: https://data.mendeley.com/datasets/zd9dxpyybg/1 PMID:29220454

Better Search Through Query Expansion Using Controlled Vocabularies and Apache Solr

Directory of Open Access Journals (Sweden)

Scott Williams

2013-04-01

Full Text Available This article describes how the University of Pennsylvania Museum of Archaeology and Anthropology (Penn Museum modified its Solr-based discovery interface to improve recall and enable end users to benefit from the power of their in-house controlled vocabularies. These modifications automatically expand the query generated by any search term that matches their controlled vocabulary to include all related alternate and narrower terms. For example, if a user enters Ohio, that search will retrieve the record for an arrowhead found in Cincinnati (a narrower term of Ohio even if that record does not include the term Ohio.

A fully automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

Science.gov (United States)

Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L

2018-01-01

The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.

SPARK: Adapting Keyword Query to Semantic Search

Science.gov (United States)

Zhou, Qi; Wang, Chong; Xiong, Miao; Wang, Haofen; Yu, Yong

Semantic search promises to provide more accurate result than present-day keyword search. However, progress with semantic search has been delayed due to the complexity of its query languages. In this paper, we explore a novel approach of adapting keywords to querying the semantic web: the approach automatically translates keyword queries into formal logic queries so that end users can use familiar keywords to perform semantic search. A prototype system named 'SPARK' has been implemented in light of this approach. Given a keyword query, SPARK outputs a ranked list of SPARQL queries as the translation result. The translation in SPARK consists of three major steps: term mapping, query graph construction and query ranking. Specifically, a probabilistic query ranking model is proposed to select the most likely SPARQL query. In the experiment, SPARK achieved an encouraging translation result.

The effect of episodic retrieval on inhibition in task switching.

Science.gov (United States)

Grange, James A; Kowalczyk, Agnieszka W; O'Loughlin, Rory

2017-08-01

Inhibition in task switching is inferred from n-2 repetition costs: the observation that ABA task switching sequences are responded to slower than CBA sequences. This is thought to reflect the persisting inhibition of Task A, which slows reactivation attempts. Mayr (2002) reported an experiment testing a critical noninhibitory account of this effect, namely episodic retrieval: If the trial parameters for Task A match across an ABA sequence, responses should be facilitated because of priming from episodic retrieval; a cost would occur if trial parameters mismatch. In a rule-switching paradigm, Mayr reported no significant difference in n-2 repetition cost when the trial parameters repeated or switched across an ABA sequence, in clear contrast to the episodic retrieval account. What remains unclear is whether successful episodic retrieval modulates the n-2 repetition cost. Across 3 experiments-including a close replication of Mayr-we find clear evidence of reduced n-2 task repetition costs when episodic retrieval is controlled. We find that the effect of episodic retrieval on the n-2 task repetition cost is increased when the cue-task relationship is made more abstract, suggesting the effect is because of interference in establishing the relevant attentional set. We also demonstrate that the episodic retrieval effect is not influenced by retrieval of low-level, perceptual, elements. Together, the data suggest the n-2 task repetition cost-typically attributable to an inhibitory mechanism-also reflects episodic retrieval effects. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Fuzzy Semantic Information Retrieval System for Transactional Applications

Directory of Open Access Journals (Sweden)

A O Ajayi

2009-09-01

Full Text Available In this paper, we present an information retrieval system based on the concept of fuzzy logic to relate vague and uncertain objects with un-sharp boundaries. The simple but comprehensive user interface of the system permits the entering of uncertain specifications in query forms. The system was modelled and simulated in a Matlab environment; its implementation was carried out using Borland C++ Builder. The result of the performance measure of the system using precision and recall rates is encouraging. Similarly, the smaller amount of more precise information retrieved by the system will positively impact the response time perceived by the users.

Improved image retrieval based on fuzzy colour feature vector

Science.gov (United States)

Ben-Ahmeida, Ahlam M.; Ben Sasi, Ahmed Y.

2013-03-01

One of Image indexing techniques is the Content-Based Image Retrieval which is an efficient way for retrieving images from the image database automatically based on their visual contents such as colour, texture, and shape. In this paper will be discuss how using content-based image retrieval (CBIR) method by colour feature extraction and similarity checking. By dividing the query image and all images in the database into pieces and extract the features of each part separately and comparing the corresponding portions in order to increase the accuracy in the retrieval. The proposed approach is based on the use of fuzzy sets, to overcome the problem of curse of dimensionality. The contribution of colour of each pixel is associated to all the bins in the histogram using fuzzy-set membership functions. As a result, the Fuzzy Colour Histogram (FCH), outperformed the Conventional Colour Histogram (CCH) in image retrieving, due to its speedy results, where were images represented as signatures that took less size of memory, depending on the number of divisions. The results also showed that FCH is less sensitive and more robust to brightness changes than the CCH with better retrieval recall values.

Query Language for Location-Based Services: A Model Checking Approach

Science.gov (United States)

Hoareau, Christian; Satoh, Ichiro

We present a model checking approach to the rationale, implementation, and applications of a query language for location-based services. Such query mechanisms are necessary so that users, objects, and/or services can effectively benefit from the location-awareness of their surrounding environment. The underlying data model is founded on a symbolic model of space organized in a tree structure. Once extended to a semantic model for modal logic, we regard location query processing as a model checking problem, and thus define location queries as hybrid logicbased formulas. Our approach is unique to existing research because it explores the connection between location models and query processing in ubiquitous computing systems, relies on a sound theoretical basis, and provides modal logic-based query mechanisms for expressive searches over a decentralized data structure. A prototype implementation is also presented and will be discussed.

Effective material parameter retrieval of anisotropic elastic metamaterials with inherent nonlocality

Science.gov (United States)

Lee, Hyung Jin; Lee, Heung Son; Ma, Pyung Sik; Kim, Yoon Young

2016-09-01

In this paper, the scattering (S-) parameter retrieval method is presented specifically for anisotropic elastic metamaterials; so far, no retrieval has been accomplished when elastic metamaterials exhibit fully anisotropic behavior. Complex constitutive property and intrinsic scattering behavior of elastic metamaterials make their characterization far more complicated than that for acoustic and electromagnetic metamaterials. In particular, elastic metamaterials generally exhibit anisotropic scattering behavior due to higher scattering modes associated with shear deformation. They also exhibit nonlocal responses to some degrees, which originate from strong multiple scattering interactions even in the long wavelength limit. Accordingly, the conventional S-parameter retrieval methods cannot be directly used for elastic metamaterials, because they determine only the diagonal components in effective tensor property. Also, the conventional methods simply use the analytic inversion formulae for the material characterization so that inherent nonlocality cannot be taken into account. To establish a retrieval method applicable to anisotropic elastic metamaterials, we propose an alternative S-parameter method to deal with full anisotropy of elastic metamaterials. To retrieve the whole effective anisotropic parameter, we utilize not only normal but also oblique wave incidences. For the retrieval, we first retrieve the ratio of the effective stiffness tensor to effective density and then determine the effective density. The proposed retrieval method is validated by characterizing the effective material parameters of various types of non-resonant anisotropic metamaterials. It is found that the whole effective parameters are retrieved consistently regardless of used retrieval conditions in spite of inherent nonlocality.

Algebra-Based Optimization of XML-Extended OLAP Queries

DEFF Research Database (Denmark)

Yin, Xuepeng; Pedersen, Torben Bach

In today’s OLAP systems, integrating fast changing data, e.g., stock quotes, physically into a cube is complex and time-consuming. The widespread use of XML makes it very possible that this data is available in XML format on the WWW; thus, making XML data logically federated with OLAP systems...... is desirable. This report presents a complete foundation for such OLAP-XML federations. This includes a prototypical query engine, a simplified query semantics based on previous work, and a complete physical algebra which enables precise modeling of the execution tasks of an OLAP-XML query. Effective algebra...

Querying and Mining Strings Made Easy

KAUST Repository

Sahli, Majed

2017-10-13

With the advent of large string datasets in several scientific and business applications, there is a growing need to perform ad-hoc analysis on strings. Currently, strings are stored, managed, and queried using procedural codes. This limits users to certain operations supported by existing procedural applications and requires manual query planning with limited tuning opportunities. This paper presents StarQL, a generic and declarative query language for strings. StarQL is based on a native string data model that allows StarQL to support a large variety of string operations and provide semantic-based query optimization. String analytic queries are too intricate to be solved on one machine. Therefore, we propose a scalable and efficient data structure that allows StarQL implementations to handle large sets of strings and utilize large computing infrastructures. Our evaluation shows that StarQL is able to express workloads of application-specific tools, such as BLAST and KAT in bioinformatics, and to mine Wikipedia text for interesting patterns using declarative queries. Furthermore, the StarQL query optimizer shows an order of magnitude reduction in query execution time.

Retrieval Architecture with Classified Query for Content Based Image Recognition

Directory of Open Access Journals (Sweden)

Rik Das

2016-01-01

Full Text Available The consumer behavior has been observed to be largely influenced by image data with increasing familiarity of smart phones and World Wide Web. Traditional technique of browsing through product varieties in the Internet with text keywords has been gradually replaced by the easy accessible image data. The importance of image data has portrayed a steady growth in application orientation for business domain with the advent of different image capturing devices and social media. The paper has described a methodology of feature extraction by image binarization technique for enhancing identification and retrieval of information using content based image recognition. The proposed algorithm was tested on two public datasets, namely, Wang dataset and Oliva and Torralba (OT-Scene dataset with 3688 images on the whole. It has outclassed the state-of-the-art techniques in performance measure and has shown statistical significance.

Signature detection and matching for document image retrieval.

Science.gov (United States)

Zhu, Guangyu; Zheng, Yefeng; Doermann, David; Jaeger, Stefan

2009-11-01

As one of the most pervasive methods of individual identification and document authentication, signatures present convincing evidence and provide an important form of indexing for effective document image processing and retrieval in a broad range of applications. However, detection and segmentation of free-form objects such as signatures from clustered background is currently an open document analysis problem. In this paper, we focus on two fundamental problems in signature-based document image retrieval. First, we propose a novel multiscale approach to jointly detecting and segmenting signatures from document images. Rather than focusing on local features that typically have large variations, our approach captures the structural saliency using a signature production model and computes the dynamic curvature of 2D contour fragments over multiple scales. This detection framework is general and computationally tractable. Second, we treat the problem of signature retrieval in the unconstrained setting of translation, scale, and rotation invariant nonrigid shape matching. We propose two novel measures of shape dissimilarity based on anisotropic scaling and registration residual error and present a supervised learning framework for combining complementary shape information from different dissimilarity metrics using LDA. We quantitatively study state-of-the-art shape representations, shape matching algorithms, measures of dissimilarity, and the use of multiple instances as query in document image retrieval. We further demonstrate our matching techniques in offline signature verification. Extensive experiments using large real-world collections of English and Arabic machine-printed and handwritten documents demonstrate the excellent performance of our approaches.

Geospatial metadata retrieval from web services

Directory of Open Access Journals (Sweden)

Ivanildo Barbosa

Full Text Available Nowadays, producers of geospatial data in either raster or vector formats are able to make them available on the World Wide Web by deploying web services that enable users to access and query on those contents even without specific software for geoprocessing. Several providers around the world have deployed instances of WMS (Web Map Service, WFS (Web Feature Service and WCS (Web Coverage Service, all of them specified by the Open Geospatial Consortium (OGC. In consequence, metadata about the available contents can be retrieved to be compared with similar offline datasets from other sources. This paper presents a brief summary and describes the matching process between the specifications for OGC web services (WMS, WFS and WCS and the specifications for metadata required by the ISO 19115 - adopted as reference for several national metadata profiles, including the Brazilian one. This process focuses on retrieving metadata about the identification and data quality packages as well as indicates the directions to retrieve metadata related to other packages. Therefore, users are able to assess whether the provided contents fit to their purposes.

Formal Concept Analysis for Information Retrieval

OpenAIRE

Qadi, Abderrahim El; Aboutajedine, Driss; Ennouary, Yassine

2010-01-01

In this paper we describe a mechanism to improve Information Retrieval (IR) on the web. The method is based on Formal Concepts Analysis (FCA) that it is makes semantical relations during the queries, and allows a reorganizing, in the shape of a lattice of concepts, the answers provided by a search engine. We proposed for the IR an incremental algorithm based on Galois lattice. This algorithm allows a formal clustering of the data sources, and the results which it turns over are classified by ...

Incentives for Delay-Constrained Data Query and Feedback in Mobile Opportunistic Crowdsensing

Directory of Open Access Journals (Sweden)

Yang Liu

2016-07-01

Full Text Available In this paper, we propose effective data collection schemes that stimulate cooperation between selfish users in mobile opportunistic crowdsensing. A query issuer generates a query and requests replies within a given delay budget. When a data provider receives the query for the first time from an intermediate user, the former replies to it and authorizes the latter as the owner of the reply. Different data providers can reply to the same query. When a user that owns a reply meets the query issuer that generates the query, it requests the query issuer to pay credits. The query issuer pays credits and provides feedback to the data provider, which gives the reply. When a user that carries a feedback meets the data provider, the data provider pays credits to the user in order to adjust its claimed expertise. Queries, replies and feedbacks can be traded between mobile users. We propose an effective mechanism to define rewards for queries, replies and feedbacks. We formulate the bargain process as a two-person cooperative game, whose solution is found by using the Nash theorem. To improve the credit circulation, we design an online auction process, in which the wealthy user can buy replies and feedbacks from the starving one using credits. We have carried out extensive simulations based on real-world traces to evaluate the proposed schemes.

Multi-Dimensional Path Queries

DEFF Research Database (Denmark)

Bækgaard, Lars

1998-01-01

to create nested path structures. We present an SQL-like query language that is based on path expressions and we show how to use it to express multi-dimensional path queries that are suited for advanced data analysis in decision support environments like data warehousing environments......We present the path-relationship model that supports multi-dimensional data modeling and querying. A path-relationship database is composed of sets of paths and sets of relationships. A path is a sequence of related elements (atoms, paths, and sets of paths). A relationship is a binary path...

Learning via Query Synthesis

KAUST Repository

Alabdulmohsin, Ibrahim

2017-01-01

Active learning is a subfield of machine learning that has been successfully used in many applications. One of the main branches of active learning is query synthe- sis, where the learning agent constructs artificial queries from scratch in order

Processing SPARQL queries with regular expressions in RDF databases

Science.gov (United States)

2011-01-01

Background As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users’ requests for extracting information from the RDF data as well as the lack of users’ knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns. PMID:21489225

Processing SPARQL queries with regular expressions in RDF databases.

Science.gov (United States)

Lee, Jinsoo; Pham, Minh-Duc; Lee, Jihwan; Han, Wook-Shin; Cho, Hune; Yu, Hwanjo; Lee, Jeong-Hoon

2011-03-29

As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users' requests for extracting information from the RDF data as well as the lack of users' knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1) We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2) We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3) We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.

Cross-Domain Shoe Retrieval with a Semantic Hierarchy of Attribute Classification Network.

Science.gov (United States)

Zhan, Huijing; Shi, Boxin; Kot, Alex C

2017-08-04

Cross-domain shoe image retrieval is a challenging problem, because the query photo from the street domain (daily life scenario) and the reference photo in the online domain (online shop images) have significant visual differences due to the viewpoint and scale variation, self-occlusion, and cluttered background. This paper proposes the Semantic Hierarchy Of attributE Convolutional Neural Network (SHOE-CNN) with a three-level feature representation for discriminative shoe feature expression and efficient retrieval. The SHOE-CNN with its newly designed loss function systematically merges semantic attributes of closer visual appearances to prevent shoe images with the obvious visual differences being confused with each other; the features extracted from image, region, and part levels effectively match the shoe images across different domains. We collect a large-scale shoe dataset composed of 14341 street domain and 12652 corresponding online domain images with fine-grained attributes to train our network and evaluate our system. The top-20 retrieval accuracy improves significantly over the solution with the pre-trained CNN features.

An Intelligent Information Retrieval Approach Based on Two Degrees of Uncertainty Fuzzy Ontology

Directory of Open Access Journals (Sweden)

Maryam Hourali

2011-01-01

Full Text Available In spite of the voluminous studies in the field of intelligent retrieval systems, effective retrieving of information has been remained an important unsolved problem. Implementations of different conceptual knowledge in the information retrieval process such as ontology have been considered as a solution to enhance the quality of results. Furthermore, the conceptual formalism supported by typical ontology may not be sufficient to represent uncertainty information due to the lack of clear-cut boundaries between concepts of the domains. To tackle this type of problems, one possible solution is to insert fuzzy logic into ontology construction process. In this article, a novel approach for fuzzy ontology generation with two uncertainty degrees is proposed. Hence, by implementing linguistic variables, uncertainty level in domain's concepts (Software Maintenance Engineering (SME domain has been modeled, and ontology relations have been modeled by fuzzy theory consequently. Then, we combined these uncertain models and proposed a new ontology with two degrees of uncertainty both in concept expression and relation expression. The generated fuzzy ontology was implemented for expansion of initial user's queries in SME domain. Experimental results showed that the proposed model has better overall retrieval performance comparing to keyword-based or crisp ontology-based retrieval systems.

Web-Scale Discovery Services Retrieve Relevant Results in Health Sciences Topics Including MEDLINE Content

Directory of Open Access Journals (Sweden)

Elizabeth Margaret Stovold

2017-06-01

Full Text Available A Review of: Hanneke, R., & O’Brien, K. K. (2016. Comparison of three web-scale discovery services for health sciences research. Journal of the Medical Library Association, 104(2, 109-117. http://dx.doi.org/10.3163/1536-5050.104.2.004 Abstract Objective – To compare the results of health sciences search queries in three web-scale discovery (WSD services for relevance, duplicate detection, and retrieval of MEDLINE content. Design – Comparative evaluation and bibliometric study. Setting – Six university libraries in the United States of America. Subjects – Three commercial WSD services: Primo, Summon, and EBSCO Discovery Service (EDS. Methods – The authors collected data at six universities, including their own. They tested each of the three WSDs at two data collection sites. However, since one of the sites was using a legacy version of Summon that was due to be upgraded, data collected for Summon at this site were considered obsolete and excluded from the analysis. The authors generated three questions for each of six major health disciplines, then designed simple keyword searches to mimic typical student search behaviours. They captured the first 20 results from each query run at each test site, to represent the first “page” of results, giving a total of 2,086 total search results. These were independently assessed for relevance to the topic. Authors resolved disagreements by discussion, and calculated a kappa inter-observer score. They retained duplicate records within the results so that the duplicate detection by the WSDs could be compared. They assessed MEDLINE coverage by the WSDs in several ways. Using precise strategies to generate a relevant set of articles, they conducted one search from each of the six disciplines in PubMed so that they could compare retrieval of MEDLINE content. These results were cross-checked against the first 20 results from the corresponding query in the WSDs. To aid investigation of overall

Using the weighted keyword model to improve information retrieval for answering biomedical questions.

Science.gov (United States)

Yu, Hong; Cao, Yong-Gang

2009-03-01

Physicians ask many complex questions during the patient encounter. Information retrieval systems that can provide immediate and relevant answers to these questions can be invaluable aids to the practice of evidence-based medicine. In this study, we first automatically identify topic keywords from ad hoc clinical questions with a Condition Random Field model that is trained over thousands of manually annotated clinical questions. We then report on a linear model that assigns query weights based on their automatically identified semantic roles: topic keywords, domain specific terms, and their synonyms. Our evaluation shows that this weighted keyword model improves information retrieval from the Text Retrieval Conference Genomics track data.

Truth Space Method for Caching Database Queries

Directory of Open Access Journals (Sweden)

S. V. Mosin

2015-01-01

Full Text Available We propose a new method of client-side data caching for relational databases with a central server and distant clients. Data are loaded into the client cache based on queries executed on the server. Every query has the corresponding DB table – the result of the query execution. These queries have a special form called "universal relational query" based on three fundamental Relational Algebra operations: selection, projection and natural join. We have to mention that such a form is the closest one to the natural language and the majority of database search queries can be expressed in this way. Besides, this form allows us to analyze query correctness by checking lossless join property. A subsequent query may be executed in a client’s local cache if we can determine that the query result is entirely contained in the cache. For this we compare truth spaces of the logical restrictions in a new user’s query and the results of the queries execution in the cache. Such a comparison can be performed analytically , without need in additional Database queries. This method may be used to define lacking data in the cache and execute the query on the server only for these data. To do this the analytical approach is also used, what distinguishes our paper from the existing technologies. We propose four theorems for testing the required conditions. The first and the third theorems conditions allow us to define the existence of required data in cache. The second and the fourth theorems state conditions to execute queries with cache only. The problem of cache data actualizations is not discussed in this paper. However, it can be solved by cataloging queries on the server and their serving by triggers in background mode. The article is published in the author’s wording.

Active learning methods for interactive image retrieval.

Science.gov (United States)

Gosselin, Philippe Henri; Cord, Matthieu

2008-07-01

Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

Optimizing Temporal Queries: Efficient Handling of Duplicates

DEFF Research Database (Denmark)

Toman, David; Bowman, Ivan Thomas

2001-01-01

, these query languages are implemented by translating temporal queries into standard relational queries. However, the compiled queries are often quite cumbersome and expensive to execute even using state-of-the- art relational products. This paper presents an optimization technique that produces more efficient...... translated SQL queries by taking into account the properties of the encoding used for temporal attributes. For concreteness, this translation technique is presented in the context of SQL/TP; however, these techniques are also applicable to other temporal query languages....

An Object-Oriented Approach of Keyword Querying over Fuzzy XML

Directory of Open Access Journals (Sweden)

Ting Li

2016-09-01

Full Text Available As the fuzzy data management has become one of the main research topics and directions, the question of how to obtain the useful information by means of keyword query from fuzzy XML documents is becoming a subject of an increasing needed investigation. Considering the keyword query methods on crisp XML documents, smallest lowest common ancestor (SLCA semantics is one of the most widely accepted semantics. When users propose the keyword query on fuzzy XML documents with the SLCA semantics, the query results are always incomplate, with low precision, and with no possibilities values returned. Most of keyword query semantics on XML documents only consider query results matching all keywords, yet users may also be interested in the query results matching partial keywords. To overcome these limitations, in this paper, we investigate how to obtain more comprehensive and meaningful results of keyword querying on fuzzy XML documents. We propose a semantics of object-oriented keyword querying on fuzzy XML documents. First, we introduce the concept of "object tree", analyze different types of matching result object trees and find the "minimum result object trees" which contain all keywords and "result object trees" which contain partial keywords. Then an object-oriented keyword query algorithm ROstack is proposed to obtain the root nodes of these matching result object trees, together with their possibilities. At last, experiments are conducted to verify the effectiveness and efficiency of our proposed algorithm.

A hybrid technique for private location-based queries with database protection

KAUST Repository

Ghinita, Gabriel

2009-01-01

Mobile devices with global positioning capabilities allow users to retrieve points of interest (POI) in their proximity. To protect user privacy, it is important not to disclose exact user coordinates to un-trusted entities that provide location-based services. Currently, there are two main approaches to protect the location privacy of users: (i) hiding locations inside cloaking regions (CRs) and (ii) encrypting location data using private information retrieval (PIR) protocols. Previous work focused on finding good trade-offs between privacy and performance of user protection techniques, but disregarded the important issue of protecting the POI dataset D. For instance, location cloaking requires large-sized CRs, leading to excessive disclosure of POIs (O(|D|) in the worst case). PIR, on the other hand, reduces this bound to , but at the expense of high processing and communication overhead. We propose a hybrid, two-step approach to private location-based queries, which provides protection for both the users and the database. In the first step, user locations are generalized to coarse-grained CRs which provide strong privacy. Next, a PIR protocol is applied with respect to the obtained query CR. To protect excessive disclosure of POI locations, we devise a cryptographic protocol that privately evaluates whether a point is enclosed inside a rectangular region. We also introduce an algorithm to efficiently support PIR on dynamic POI sub-sets. Our method discloses O(1) POI, orders of magnitude fewer than CR- or PIR-based techniques. Experimental results show that the hybrid approach is scalable in practice, and clearly outperforms the pure-PIR approach in terms of computational and communication overhead. © 2009 Springer Berlin Heidelberg.

Pro PHP and jQuery

CERN Document Server

Lengstorf, Jason

2010-01-01

This book is for intermediate programmers interested in building AJAX web applications using jQuery and PHP. Along with teaching some advanced PHP techniques, it will teach you how to take your dynamic applications to the next level by adding a JavaScript layer with jQuery. * Learn to utilize built-in PHP functions to build calendar tools.* Learn how jQuery can be used for AJAX, animation, client-side validation, and more.What you'll learn* Use PHP to build a calendar application that allows users to post, view, edit, and delete events.* Use jQuery to allow the calendar app to be viewed and ed

Query recommendation for children

NARCIS (Netherlands)

Duarte Torres, Sergio; Hiemstra, Djoerd; Weber, Ingmar; Serdyukov, Pavel

2012-01-01

One of the biggest problems that children experience while searching the web occurs during the query formulation process. Children have been found to struggle formulating queries based on keywords given their limited vocabulary and their difficulty to choose the right keywords. In this work we

Processing SPARQL queries with regular expressions in RDF databases

Directory of Open Access Journals (Sweden)

Cho Hune

2011-03-01

Full Text Available Abstract Background As the Resource Description Framework (RDF data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf or Bio2RDF (bio2rdf.org, SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users’ requests for extracting information from the RDF data as well as the lack of users’ knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph. Results In this paper, we propose a novel framework for supporting regular expression processing in SPARQL query. Our contributions can be summarized as follows. 1 We propose an efficient framework for processing SPARQL queries with regular expression patterns in RDF databases. 2 We propose a cost model in order to adapt the proposed framework in the existing query optimizers. 3 We build a prototype for the proposed framework in C++ and conduct extensive experiments demonstrating the efficiency and effectiveness of our technique. Conclusions Experiments with a full-blown RDF engine show that our framework outperforms the existing ones by up to two orders of magnitude in processing SPARQL queries with regular expression patterns.

Can Internet search queries help to predict stock market volatility?

OpenAIRE

Dimpfl, Thomas; Jank, Stephan

2011-01-01

This paper studies the dynamics of stock market volatility and retail investor attention measured by internet search queries. We find a strong co-movement of stock market indices’ realized volatility and the search queries for their names. Furthermore, Granger causality is bi-directional: high searches follow high volatility, and high volatility follows high searches. Using the latter feedback effect to predict volatility we find that search queries contain additional information about market...

A prototype feature system for feature retrieval using relationships

Science.gov (United States)

Choi, J.; Usery, E.L.

2009-01-01

Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

Interfering effects of retrieval in learning new information.

Science.gov (United States)

Finn, Bridgid; Roediger, Henry L

2013-11-01

In 7 experiments, we explored the role of retrieval in associative updating, that is, in incorporating new information into an associative memory. We tested the hypothesis that retrieval would facilitate incorporating a new contextual detail into a learned association. Participants learned 3 pieces of information-a person's face, name, and profession (in Experiments 1-5). In the 1st phase, participants in all conditions learned faces and names. In the 2nd phase, participants either restudied the face-name pair (the restudy condition) or were given the face and asked to retrieve the name (the test condition). In the 3rd phase, professions were presented for study just after restudy or testing. Our prediction was that the new information (the profession) would be more readily learned following retrieval of the face-name association compared to restudy of the face-name association. However, we found that the act of retrieval generally undermined acquisition of new associations rather than facilitating them. This detrimental effect emerged on both immediate and delayed tests. Further, the effect was not due to selective attention to feedback because we found impairment whether or not feedback was provided after the Phase 2 test. The data are novel in showing that the act of retrieving information can inhibit the ability to learn new information shortly thereafter. The results are difficult to accommodate within current theories that mostly emphasize benefits of retrieval for learning. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Differentiation of subsequent memory effects between retrieval practice and elaborative study.

Science.gov (United States)

Liu, Yi; Rosburg, Timm; Gao, Chuanji; Weber, Christine; Guo, Chunyan

2017-07-01

Retrieval practice enhances memory retention more than re-studying. The underlying mechanisms of this retrieval practice effect have remained widely unclear. According to the elaborative retrieval hypothesis, activation of elaborative information occurs to a larger extent during testing than re-studying. In contrast, the episodic context account has suggested that recollecting prior episodic information (especially the temporal context) contributes to memory retention. To adjudicate the distinction between these two accounts, the present study used the classical retrieval practice effect paradigm to compare retrieval practice and elaborative study. In an initial behavioral experiment, retrieval practice produced greater retention than elaboration and re-studying in a one-week delayed test. In a subsequent event-related potential (ERP) experiment, retrieval practice resulted in reliably superior accuracy in the delayed test compared to elaborative study. In the ERPs, a frontally distributed subsequent memory effect (SME), starting at 300ms, occurred in the elaborative study condition, but not in the retrieval practice condition. A parietal SME emerged in the retrieval practice condition from 500 to 700ms, but was absent in the elaborative study condition. After 700ms, a late SME was present in the retrieval practice condition, but not in the elaborative study condition. Moreover, SMEs lasted longer in retrieval practice than in elaboration. The frontal SME in the elaborative study condition might be related to semantic processing or working memory-based elaboration, whereas the parietal and widespread SME in the retrieval practice condition might be associated with episodic recollection processes. These findings contradict the elaborative retrieval theory, and suggest that contextual recollection rather than activation of semantic information contributes to the retrieval practice effect, supporting the episodic context account. Copyright © 2017. Published by

Approximate and exact hybrid algorithms for private nearest-neighbor queries with database protection

KAUST Repository

Ghinita, Gabriel; Kalnis, Panos; Kantarcioǧlu, Murâ t; Bertino, Elisa

2010-01-01

Mobile devices with global positioning capabilities allow users to retrieve points of interest (POI) in their proximity. To protect user privacy, it is important not to disclose exact user coordinates to un-trusted entities that provide location-based services. Currently, there are two main approaches to protect the location privacy of users: (i) hiding locations inside cloaking regions (CRs) and (ii) encrypting location data using private information retrieval (PIR) protocols. Previous work focused on finding good trade-offs between privacy and performance of user protection techniques, but disregarded the important issue of protecting the POI dataset D. For instance, location cloaking requires large-sized CRs, leading to excessive disclosure of POIs (O({pipe}D{pipe}) in the worst case). PIR, on the other hand, reduces this bound to O(√{pipe}D{pipe}), but at the expense of high processing and communication overhead. We propose hybrid, two-step approaches for private location-based queries which provide protection for both the users and the database. In the first step, user locations are generalized to coarse-grained CRs which provide strong privacy. Next, a PIR protocol is applied with respect to the obtained query CR. To protect against excessive disclosure of POI locations, we devise two cryptographic protocols that privately evaluate whether a point is enclosed inside a rectangular region or a convex polygon. We also introduce algorithms to efficiently support PIR on dynamic POI sub-sets. We provide solutions for both approximate and exact NN queries. In the approximate case, our method discloses O(1) POI, orders of magnitude fewer than CR- or PIR-based techniques. For the exact case, we obtain optimal disclosure of a single POI, although with slightly higher computational overhead. Experimental results show that the hybrid approaches are scalable in practice, and outperform the pure-PIR approach in terms of computational and communication overhead. © 2010

Approximate and exact hybrid algorithms for private nearest-neighbor queries with database protection

KAUST Repository

Ghinita, Gabriel

2010-12-15

Mobile devices with global positioning capabilities allow users to retrieve points of interest (POI) in their proximity. To protect user privacy, it is important not to disclose exact user coordinates to un-trusted entities that provide location-based services. Currently, there are two main approaches to protect the location privacy of users: (i) hiding locations inside cloaking regions (CRs) and (ii) encrypting location data using private information retrieval (PIR) protocols. Previous work focused on finding good trade-offs between privacy and performance of user protection techniques, but disregarded the important issue of protecting the POI dataset D. For instance, location cloaking requires large-sized CRs, leading to excessive disclosure of POIs (O({pipe}D{pipe}) in the worst case). PIR, on the other hand, reduces this bound to O(√{pipe}D{pipe}), but at the expense of high processing and communication overhead. We propose hybrid, two-step approaches for private location-based queries which provide protection for both the users and the database. In the first step, user locations are generalized to coarse-grained CRs which provide strong privacy. Next, a PIR protocol is applied with respect to the obtained query CR. To protect against excessive disclosure of POI locations, we devise two cryptographic protocols that privately evaluate whether a point is enclosed inside a rectangular region or a convex polygon. We also introduce algorithms to efficiently support PIR on dynamic POI sub-sets. We provide solutions for both approximate and exact NN queries. In the approximate case, our method discloses O(1) POI, orders of magnitude fewer than CR- or PIR-based techniques. For the exact case, we obtain optimal disclosure of a single POI, although with slightly higher computational overhead. Experimental results show that the hybrid approaches are scalable in practice, and outperform the pure-PIR approach in terms of computational and communication overhead. © 2010

Learning via Query Synthesis

KAUST Repository

Alabdulmohsin, Ibrahim Mansour

2017-05-07

Active learning is a subfield of machine learning that has been successfully used in many applications. One of the main branches of active learning is query synthe- sis, where the learning agent constructs artificial queries from scratch in order to reveal sensitive information about the underlying decision boundary. It has found applications in areas, such as adversarial reverse engineering, automated science, and computational chemistry. Nevertheless, the existing literature on membership query synthesis has, generally, focused on finite concept classes or toy problems, with a limited extension to real-world applications. In this thesis, I develop two spectral algorithms for learning halfspaces via query synthesis. The first algorithm is a maximum-determinant convex optimization method while the second algorithm is a Markovian method that relies on Khachiyan’s classical update formulas for solving linear programs. The general theme of these methods is to construct an ellipsoidal approximation of the version space and to synthesize queries, afterward, via spectral decomposition. Moreover, I also describe how these algorithms can be extended to other settings as well, such as pool-based active learning. Having demonstrated that halfspaces can be learned quite efficiently via query synthesis, the second part of this thesis proposes strategies for mitigating the risk of reverse engineering in adversarial environments. One approach that can be used to render query synthesis algorithms ineffective is to implement a randomized response. In this thesis, I propose a semidefinite program (SDP) for learning a distribution of classifiers, subject to the constraint that any individual classifier picked at random from this distributions provides reliable predictions with a high probability. This algorithm is, then, justified both theoretically and empirically. A second approach is to use a non-parametric classification method, such as similarity-based classification. In this

VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans

Science.gov (United States)

Wang, Song; Gupta, Chetan; Mehta, Abhay

There are data streams all around us that can be harnessed for tremendous business and personal advantage. For an enterprise-level stream processing system such as CHAOS [1] (Continuous, Heterogeneous Analytic Over Streams), handling of complex query plans with resource constraints is challenging. While several scheduling strategies exist for stream processing, efficient scheduling of complex DAG query plans is still largely unsolved. In this paper, we propose a novel execution scheme for scheduling complex directed acyclic graph (DAG) query plans with meta-data enriched stream tuples. Our solution, called Virtual Pipelined Chain (or VPipe Chain for short), effectively extends the "Chain" pipelining scheduling approach to complex DAG query plans.

jQuery Tools UI Library

CERN Document Server

Libby, Alex

2012-01-01

A practical tutorial with powerful yet simple projects that are quick to implement. This book is aimed at developers who have prior jQuery knowledge, but may not have any prior experience with jQuery Tools. It is possible that they may have started with the basics of jQuery Tools, but want to learn more about how it can be used, as well as get ideas for future projects.

Joint Top-K Spatial Keyword Query Processing

DEFF Research Database (Denmark)

Wu, Dingming; Yiu, Man Lung; Cong, Gao

2012-01-01

Web users and content are increasingly being geopositioned, and increased focus is being given to serving local content in response to web queries. This development calls for spatial keyword queries that take into account both the locations and textual descriptions of content. We study the effici......Web users and content are increasingly being geopositioned, and increased focus is being given to serving local content in response to web queries. This development calls for spatial keyword queries that take into account both the locations and textual descriptions of content. We study...... the efficient, joint processing of multiple top-k spatial keyword queries. Such joint processing is attractive during high query loads and also occurs when multiple queries are used to obfuscate a user's true query. We propose a novel algorithm and index structure for the joint processing of top-k spatial...... keyword queries. Empirical studies show that the proposed solution is efficient on real data sets. We also offer analytical studies on synthetic data sets to demonstrate the efficiency of the proposed solution. Index Terms IEEE Terms Electronic mail , Google , Indexes , Joints , Mobile communication...

Individual Differences in the Effects of Retrieval from Long-Term Memory

Science.gov (United States)

Brewer, Gene A.; Unsworth, Nash

2012-01-01

The current study examined individual differences in the effects of retrieval from long-term memory (i.e., the testing effect). The effects of retrieving from memory make tested information more accessible for future retrieval attempts. Despite the broad applied ramifications of such a potent memorization technique there is a paucity of research…

Efficient and Flexible KNN Query Processing in Real-Life Road Networks

DEFF Research Database (Denmark)

Lu, Yang; Bui, Bin; Zhao, Jiakui

2008-01-01

are included into the RNG index, which enables the index to support both distance-based and time-based KNN queries and continuous KNN queries. Our work extends previous ones by taking into account more practical scenarios, such as complexities in real-life road networks and time-based KNN queries. Extensive......Along with the developments of mobile services, effectively modeling road networks and efficiently indexing and querying network constrained objects has become a challenging problem. In this paper, we first introduce a road network model which captures real-life road networks better than previous...

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

Science.gov (United States)

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

A contribution to semantic indexing and retrieval based on FCA - An application to song datasets

OpenAIRE

Codocedo , Victor; Lykourentzou , Ioanna; Napoli , Amedeo

2012-01-01

International audience; Semantic indexing and retrieval is an important research area, as the available amount of information on the Web is growing more and more. In this paper, we introduce an original approach to semantic indexing and retrieval based on Formal Concept Analysis. The concept lattice is used as a semantic index and we propose an original algorithm for traversing the lattice and answering user queries. This framework has been used and evaluated on a song dataset.

Research Issues in Mobile Querying

DEFF Research Database (Denmark)

Breunig, M.; Jensen, Christian Søndergaard; Klein, M.

2004-01-01

This document reports on key aspects of the discussions conducted within the working group. In particular, the document aims to offer a structured and somewhat digested summary of the group's discussions. The document first offers concepts that enable characterization of "mobile queries" as well...... as the types of systems that enable such queries. It explores the notion of context in mobile queries. The document ends with a few observations, mainly regarding challenges....

Measuring and Predicting Tag Importance for Image Retrieval.

Science.gov (United States)

Li, Shangwen; Purushotham, Sanjay; Chen, Chen; Ren, Yuzhuo; Kuo, C-C Jay

2017-12-01

Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.

On tractable query evaluation for SPARQL

OpenAIRE

Mengel, Stefan; Skritek, Sebastian

2017-01-01

Despite much work within the last decade on foundational properties of SPARQL - the standard query language for RDF data - rather little is known about the exact limits of tractability for this language. In particular, this is the case for SPARQL queries that contain the OPTIONAL-operator, even though it is one of the most intensively studied features of SPARQL. The aim of our work is to provide a more thorough picture of tractable classes of SPARQL queries. In general, SPARQL query evaluatio...

Man vs. Machine: Differences in SPARQL Queries

NARCIS (Netherlands)

Rietveld, L.; Hoekstra, R.

2014-01-01

Server-side SPARQL query logs have been a topic of study for some time now. The USEWOD collection of query logs is currently the primary source of information for researchers. A recurring problem is that these logs leave application queries and queries created by humans indistinguishable. In this

On the Performance of Medical Information Retrieval using MeSH Terms – A Survey

Directory of Open Access Journals (Sweden)

Swetha S

2014-09-01

Full Text Available Internet users have increased everywhere. Searching and retrieving documents is a common thing nowadays. Retrieving related documents from the search engines are difficult task. To retrieve correct documents, knowledge about the search topic is essential. Even though separate search engines are there to retrieve medical documents the users are not familiar with MeSH terms (Medical Subject Heading. So, both the search browser and the MeSH terms have to be integrated to make the search effective and efficient. To implement this integration, SimpleMed and MeSHMed were introduced. The MeSH terms have to be ranked to know how frequently it has been used and to know the importance of the MeSH terms. To rank it a semi – automated tool called MeSHy was developed. The terms were extracted, filtered, ranked and displayed to the user. Classifiers have to be constructed to label the documents as health and non – health. Three strategies were used to classify them. The errors that are commonly done by the users have to be found out. It was calculated based on the queries presented by the user to the search browser.

How Good Are Query Optimizers, Really?

NARCIS (Netherlands)

Leis, Viktor; Gubichev, Andrey; Mirchev, Atanas; Boncz, Peter; Kemper, Alfons; Neumann, Thomas

2016-01-01

Finding a good join order is crucial for query performance. In this paper, we introduce the Join Order Benchmark (JOB) and experimentally revisit the main components in the classic query optimizer architecture using a complex, real-world data set and realistic multi-join queries. We investigate the

Querying XML Data with SPARQL

Science.gov (United States)

Bikakis, Nikos; Gioldasis, Nektarios; Tsinaraki, Chrisa; Christodoulakis, Stavros

SPARQL is today the standard access language for Semantic Web data. In the recent years XML databases have also acquired industrial importance due to the widespread applicability of XML in the Web. In this paper we present a framework that bridges the heterogeneity gap and creates an interoperable environment where SPARQL queries are used to access XML databases. Our approach assumes that fairly generic mappings between ontology constructs and XML Schema constructs have been automatically derived or manually specified. The mappings are used to automatically translate SPARQL queries to semantically equivalent XQuery queries which are used to access the XML databases. We present the algorithms and the implementation of SPARQL2XQuery framework, which is used for answering SPARQL queries over XML databases.

Optimizing queries in distributed systems

Directory of Open Access Journals (Sweden)

Ion LUNGU

2006-01-01

Full Text Available This research presents the main elements of query optimizations in distributed systems. First, data architecture according with system level architecture in a distributed environment is presented. Then the architecture of a distributed database management system (DDBMS is described on conceptual level followed by the presentation of the distributed query execution steps on these information systems. The research ends with presentation of some aspects of distributed database query optimization and strategies used for that.

Advanced Query Formulation in Deductive Databases.

Science.gov (United States)

Niemi, Timo; Jarvelin, Kalervo

1992-01-01

Discusses deductive databases and database management systems (DBMS) and introduces a framework for advanced query formulation for end users. Recursive processing is described, a sample extensional database is presented, query types are explained, and criteria for advanced query formulation from the end user's viewpoint are examined. (31…

Deep Correlated Holistic Metric Learning for Sketch-Based 3D Shape Retrieval.

Science.gov (United States)

Dai, Guoxian; Xie, Jin; Fang, Yi

2018-07-01

How to effectively retrieve desired 3D models with simple queries is a long-standing problem in computer vision community. The model-based approach is quite straightforward but nontrivial, since people could not always have the desired 3D query model available by side. Recently, large amounts of wide-screen electronic devices are prevail in our daily lives, which makes the sketch-based 3D shape retrieval a promising candidate due to its simpleness and efficiency. The main challenge of sketch-based approach is the huge modality gap between sketch and 3D shape. In this paper, we proposed a novel deep correlated holistic metric learning (DCHML) method to mitigate the discrepancy between sketch and 3D shape domains. The proposed DCHML trains two distinct deep neural networks (one for each domain) jointly, which learns two deep nonlinear transformations to map features from both domains into a new feature space. The proposed loss, including discriminative loss and correlation loss, aims to increase the discrimination of features within each domain as well as the correlation between different domains. In the new feature space, the discriminative loss minimizes the intra-class distance of the deep transformed features and maximizes the inter-class distance of the deep transformed features to a large margin within each domain, while the correlation loss focused on mitigating the distribution discrepancy across different domains. Different from existing deep metric learning methods only with loss at the output layer, our proposed DCHML is trained with loss at both hidden layer and output layer to further improve the performance by encouraging features in the hidden layer also with desired properties. Our proposed method is evaluated on three benchmarks, including 3D Shape Retrieval Contest 2013, 2014, and 2016 benchmarks, and the experimental results demonstrate the superiority of our proposed method over the state-of-the-art methods.

Ranked retrieval of Computational Biology models.

Science.gov (United States)

Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

2010-08-11

The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

Dynamic Planar Range Maxima Queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Tsakalidis, Konstantinos

2011-01-01

We consider the dynamic two-dimensional maxima query problem. Let P be a set of n points in the plane. A point is maximal if it is not dominated by any other point in P. We describe two data structures that support the reporting of the t maximal points that dominate a given query point, and allow...... for insertions and deletions of points in P. In the pointer machine model we present a linear space data structure with O(logn + t) worst case query time and O(logn) worst case update time. This is the first dynamic data structure for the planar maxima dominance query problem that achieves these bounds...... are integers in the range U = {0, …,2 w  − 1 }. We present a linear space data structure that supports 3-sided range maxima queries in O(logn/loglogn+t) worst case time and updates in O(logn/loglogn) worst case time. These are the first sublogarithmic worst case bounds for all operations in the RAM model....

Generating region proposals for histopathological whole slide image retrieval.

Science.gov (United States)

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu; Shi, Jun

2018-06-01

Content-based image retrieval is an effective method for histopathological image analysis. However, given a database of huge whole slide images (WSIs), acquiring appropriate region-of-interests (ROIs) for training is significant and difficult. Moreover, histopathological images can only be annotated by pathologists, resulting in the lack of labeling information. Therefore, it is an important and challenging task to generate ROIs from WSI and retrieve image with few labels. This paper presents a novel unsupervised region proposing method for histopathological WSI based on Selective Search. Specifically, the WSI is over-segmented into regions which are hierarchically merged until the WSI becomes a single region. Nucleus-oriented similarity measures for region mergence and Nucleus-Cytoplasm color space for histopathological image are specially defined to generate accurate region proposals. Additionally, we propose a new semi-supervised hashing method for image retrieval. The semantic features of images are extracted with Latent Dirichlet Allocation and transformed into binary hashing codes with Supervised Hashing. The methods are tested on a large-scale multi-class database of breast histopathological WSIs. The results demonstrate that for one WSI, our region proposing method can generate 7.3 thousand contoured regions which fit well with 95.8% of the ROIs annotated by pathologists. The proposed hashing method can retrieve a query image among 136 thousand images in 0.29 s and reach precision of 91% with only 10% of images labeled. The unsupervised region proposing method can generate regions as predictions of lesions in histopathological WSI. The region proposals can also serve as the training samples to train machine-learning models for image retrieval. The proposed hashing method can achieve fast and precise image retrieval with small amount of labels. Furthermore, the proposed methods can be potentially applied in online computer-aided-diagnosis systems. Copyright

Nearest Neighbor Queries in Road Networks

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Kolar, Jan; Pedersen, Torben Bach

2003-01-01

in road networks. Such queries may be of use in many services. Specifically, we present an easily implementable data model that serves well as a foundation for such queries. We also present the design of a prototype system that implements the queries based on the data model. The algorithm used...

Fingerprinting Keywords in Search Queries over Tor

Directory of Open Access Journals (Sweden)

Oh Se Eun

2017-10-01

Full Text Available Search engine queries contain a great deal of private and potentially compromising information about users. One technique to prevent search engines from identifying the source of a query, and Internet service providers (ISPs from identifying the contents of queries is to query the search engine over an anonymous network such as Tor.

Advanced Query and Data Mining Capabilities for MaROS

Science.gov (United States)

Wang, Paul; Wallick, Michael N.; Allard, Daniel A.; Gladden, Roy E.; Hy, Franklin H.

2013-01-01

The Mars Relay Operational Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay network. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. As part of MaROS, the innovators have developed and implemented a feature set that operates on several levels of the software architecture. This new feature is an advanced querying capability through either the Web-based user interface, or through a back-end REST interface to access all of the data gathered from the network. This software is not meant to replace the REST interface, but to augment and expand the range of available data. The current REST interface provides specific data that is used by the MaROS Web application to display and visualize the information; however, the returned information from the REST interface has typically been pre-processed to return only a subset of the entire information within the repository, particularly only the information that is of interest to the GUI (graphical user interface). The new, advanced query and data mining capabilities allow users to retrieve the raw data and/or to perform their own data processing. The query language used to access the repository is a restricted subset of the structured query language (SQL) that can be built safely from the Web user interface, or entered as freeform SQL by a user. The results are returned in a CSV (Comma Separated Values) format for easy exporting to third party tools and applications that can be used for data mining or user-defined visualization and interpretation. This is the first time that a service is capable of providing access to all cross-project relay data from a single Web resource. Because MaROS contains the data for a variety of missions from the Mars network, which span both NASA and ESA, the software also establishes an access control list (ACL) on each data record

Adding Query Privacy to Robust DHTs

DEFF Research Database (Denmark)

Backes, Michael; Goldberg, Ian; Kate, Aniket

2011-01-01

intermediate peers that (help to) route the queries towards their destinations. In this paper, we satisfy this requirement by presenting an approach for providing privacy for the keys in DHT queries. We use the concept of oblivious transfer (OT) in communication over DHTs to preserve query privacy without...... of obtaining query privacy over robust DHTs. Finally, we compare the performance of our privacy-preserving protocols with their more privacy-invasive counterparts. We observe that there is no increase in the message complexity and only a small overhead in the computational complexity....

QUERY SUPPORT FOR GMZ

Directory of Open Access Journals (Sweden)

A. Khandelwal

2017-07-01

Full Text Available Generic text-based compression models are simple and fast but there are two issues that needs to be addressed. They cannot leverage the structure that exists in data to achieve better compression and there is an unnecessary decompression step before the user can actually use the data. To address these issues, we came up with GMZ, a lossless compression model aimed at achieving high compression ratios. The decision to design GMZ (Khandelwal and Rajan, 2017 exclusively for GML's Simple Features Profile (SFP seems fair because of the high use of SFP in WFS and that it facilitates high optimisation of the compression model. This is an extension of our work on GMZ. In a typical server-client model such as Web Feature Service, the server is the primary creator and provider of GML, and therefore, requires compression and query capabilities. On the other hand, the client is the primary consumer of GML, and therefore, requires decompression and visualisation capabilities. In the first part of our work, we demonstrated compression using a python script that can be plugged in a server architecture, and decompression and visualisation in a web browser using a Firefox addon. The focus of this work is to develop the already existing tools to provide query capability to server. Our model provides the ability to decompress individual features in isolation, which is an essential requirement for realising query in compressed state. We con - struct an R-Tree index for spatial data and a custom index for non-spatial data and store these in a separate index file to prevent alter - ing the compression model. This facilitates independent use of compressed GMZ file where index can be constructed when required. The focus of this work is the bounding-box or range query commonly used in webGIS with provision for other spatial and non-spatial queries. The decrement in compression ratios due to the new index file is in the range of 1–3 percent which is trivial considering

Ranking Queries on Uncertain Data

CERN Document Server

Hua, Ming

2011-01-01

Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data. Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorith

Recommendation Sets and Choice Queries

DEFF Research Database (Denmark)

Viappiani, Paolo Renato; Boutilier, Craig

2011-01-01

Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query users about their preferences and offer recommendations based on the system's belief about the user's utility function. We analyze the connection between...... the problem of generating optimal recommendation sets and the problem of generating optimal choice queries, considering both Bayesian and regret-based elicitation. Our results show that, somewhat surprisingly, under very general circumstances, the optimal recommendation set coincides with the optimal query....

Predecessor queries in dynamic integer sets

DEFF Research Database (Denmark)

Brodal, Gerth Stølting

1997-01-01

We consider the problem of maintaining a set of n integers in the range 0.2w–1 under the operations of insertion, deletion, predecessor queries, minimum queries and maximum queries on a unit cost RAM with word size w bits. Let f (n) be an arbitrary nondecreasing smooth function satisfying n...

Spatio-temporal databases complex motion pattern queries

CERN Document Server

Vieira, Marcos R

2013-01-01

This brief presents several new query processing techniques, called complex motion pattern queries, specifically designed for very large spatio-temporal databases of moving objects. The brief begins with the definition of flexible pattern queries, which are powerful because of the integration of variables and motion patterns. This is followed by a summary of the expressive power of patterns and flexibility of pattern queries. The brief then present the Spatio-Temporal Pattern System (STPS) and density-based pattern queries. STPS databases contain millions of records with information about mobi

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

Science.gov (United States)

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

CrossQuery: a web tool for easy associative querying of transcriptome data.

Directory of Open Access Journals (Sweden)

Toni U Wagner

Full Text Available Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types.

CrossQuery: a web tool for easy associative querying of transcriptome data.

Science.gov (United States)

Wagner, Toni U; Fischer, Andreas; Thoma, Eva C; Schartl, Manfred

2011-01-01

Enormous amounts of data are being generated by modern methods such as transcriptome or exome sequencing and microarray profiling. Primary analyses such as quality control, normalization, statistics and mapping are highly complex and need to be performed by specialists. Thereafter, results are handed back to biomedical researchers, who are then confronted with complicated data lists. For rather simple tasks like data filtering, sorting and cross-association there is a need for new tools which can be used by non-specialists. Here, we describe CrossQuery, a web tool that enables straight forward, simple syntax queries to be executed on transcriptome sequencing and microarray datasets. We provide deep-sequencing data sets of stem cell lines derived from the model fish Medaka and microarray data of human endothelial cells. In the example datasets provided, mRNA expression levels, gene, transcript and sample identification numbers, GO-terms and gene descriptions can be freely correlated, filtered and sorted. Queries can be saved for later reuse and results can be exported to standard formats that allow copy-and-paste to all widespread data visualization tools such as Microsoft Excel. CrossQuery enables researchers to quickly and freely work with transcriptome and microarray data sets requiring only minimal computer skills. Furthermore, CrossQuery allows growing association of multiple datasets as long as at least one common point of correlated information, such as transcript identification numbers or GO-terms, is shared between samples. For advanced users, the object-oriented plug-in and event-driven code design of both server-side and client-side scripts allow easy addition of new features, data sources and data types.

Multi-Dimensional Top-k Dominating Queries

DEFF Research Database (Denmark)

Yiu, Man Lung; Mamoulis, Nikos

2009-01-01

The top-k dominating query returns k data objects which dominate the highest number of objects in a dataset. This query is an important tool for decision support since it provides data analysts an intuitive way for finding significant objects. In addition, it combines the advantages of top......-k and skyline queries without sharing their disadvantages: (i) the output size can be controlled, (ii) no ranking functions need to be specified by users, and (iii) the result is independent of the scales at different dimensions. Despite their importance, top-k dominating queries have not received adequate...

Query optimization over crowdsourced data

KAUST Repository

Park, Hyunjung; Widom, Jennifer

2013-01-01

Deco is a comprehensive system for answering declarative queries posed over stored relational data together with data obtained on-demand from the crowd. In this paper we describe Deco's cost-based query optimizer, building on Deco's data model

jQuery UI 1.10 the user interface library for jQuery

CERN Document Server

Libby, Alex

2013-01-01

This book consists of an easy-to-follow, example-based approach that leads you step-by-step through the implementation and customization of each library component.This book is for frontend designers and developers who need to learn how to use jQuery UI quickly. To get the most out of this book, you should have a good working knowledge of HTML, CSS, and JavaScript, and should ideally be comfortable using jQuery.

Optimal Planar Orthogonal Skyline Counting Queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Larsen, Kasper Green

2014-01-01

counting queries, i.e. given a query rectangle R to report the size of the skyline of P\\cap R. We present a data structure for storing n points with integer coordinates having query time O(lg n/lglg n) and space usage O(n). The model of computation is a unit cost RAM with logarithmic word size. We prove...

A Fuzzy Semantic Information Retrieval System for Transactional Applications

OpenAIRE

A O Ajayi; H A Soriyan; G A Aderounmu

2009-01-01

In this paper, we present an information retrieval system based on the concept of fuzzy logic to relate vague and uncertain objects with un-sharp boundaries. The simple but comprehensive user interface of the system permits the entering of uncertain specifications in query forms. The system was modelled and simulated in a Matlab environment; its implementation was carried out using Borland C++ Builder. The result of the performance measure of the system using precision and recall rates is enc...

Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization.

Science.gov (United States)

Luo, Jake; Chen, Weiheng; Wu, Min; Weng, Chunhua

2017-12-01

Prior studies of clinical trial planning indicate that it is crucial to search and screen recruitment sites before starting to enroll participants. However, currently there is no systematic method developed to support clinical investigators to search candidate recruitment sites according to their interested clinical trial factors. In this study, we aim at developing a new approach to integrating the location data of over one million heterogeneous recruitment sites that are stored in clinical trial documents. The integrated recruitment location data can be searched and visualized using a map-based information retrieval method. The method enables systematic search and analysis of recruitment sites across a large amount of clinical trials. The location data of more than 1.4 million recruitment sites of over 183,000 clinical trials was normalized and integrated using a geocoding method. The integrated data can be used to support geographic information retrieval of recruitment sites. Additionally, the information of over 6000 clinical trial target disease conditions and close to 4000 interventions was also integrated into the system and linked to the recruitment locations. Such data integration enabled the construction of a novel map-based query system. The system will allow clinical investigators to search and visualize candidate recruitment sites for clinical trials based on target conditions and interventions. The evaluation results showed that the coverage of the geographic location mapping for the 1.4 million recruitment sites was 99.8%. The evaluation of 200 randomly retrieved recruitment sites showed that the correctness of geographic information mapping was 96.5%. The recruitment intensities of the top 30 countries were also retrieved and analyzed. The data analysis results indicated that the recruitment intensity varied significantly across different countries and geographic areas. This study contributed a new data processing framework to extract and integrate

Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization

Science.gov (United States)

Luo, Jake; Chen, Weiheng; Wu, Min; Weng, Chunhua

2018-01-01

Background Prior studies of clinical trial planning indicate that it is crucial to search and screen recruitment sites before starting to enroll participants. However, currently there is no systematic method developed to support clinical investigators to search candidate recruitment sites according to their interested clinical trial factors. Objective In this study, we aim at developing a new approach to integrating the location data of over one million heterogeneous recruitment sites that are stored in clinical trial documents. The integrated recruitment location data can be searched and visualized using a map-based information retrieval method. The method enables systematic search and analysis of recruitment sites across a large amount of clinical trials. Methods The location data of more than 1.4 million recruitment sites of over 183,000 clinical trials was normalized and integrated using a geocoding method. The integrated data can be used to support geographic information retrieval of recruitment sites. Additionally, the information of over 6000 clinical trial target disease conditions and close to 4000 interventions was also integrated into the system and linked to the recruitment locations. Such data integration enabled the construction of a novel map-based query system. The system will allow clinical investigators to search and visualize candidate recruitment sites for clinical trials based on target conditions and interventions. Results The evaluation results showed that the coverage of the geographic location mapping for the 1.4 million recruitment sites was 99.8%. The evaluation of 200 randomly retrieved recruitment sites showed that the correctness of geographic information mapping was 96.5%. The recruitment intensities of the top 30 countries were also retrieved and analyzed. The data analysis results indicated that the recruitment intensity varied significantly across different countries and geographic areas. Conclusion This study contributed a new

Working memory capacity predicts the beneficial effect of selective memory retrieval.

Science.gov (United States)

Schlichting, Andreas; Aslan, Alp; Holterman, Christoph; Bäuml, Karl-Heinz T

2015-01-01

Selective retrieval of some studied items can both impair and improve recall of the other items. This study examined the role of working memory capacity (WMC) for the two effects of memory retrieval. Participants studied an item list consisting of predefined target and nontarget items. After study of the list, half of the participants performed an imagination task supposed to induce a change in mental context, whereas the other half performed a counting task which does not induce such context change. Following presentation of a second list, memory for the original list's target items was tested, either with or without preceding retrieval of the list's nontarget items. Consistent with previous work, preceding nontarget retrieval impaired target recall in the absence of the context change, but improved target recall in its presence. In particular, there was a positive relationship between WMC and the beneficial, but not the detrimental effect of memory retrieval. On the basis of the view that the beneficial effect of memory retrieval reflects context-reactivation processes, the results indicate that individuals with higher WMC are better able to capitalise on retrieval-induced context reactivation than individuals with lower WMC.

PAQ: Persistent Adaptive Query Middleware for Dynamic Environments

Science.gov (United States)

Rajamani, Vasanth; Julien, Christine; Payton, Jamie; Roman, Gruia-Catalin

Pervasive computing applications often entail continuous monitoring tasks, issuing persistent queries that return continuously updated views of the operational environment. We present PAQ, a middleware that supports applications' needs by approximating a persistent query as a sequence of one-time queries. PAQ introduces an integration strategy abstraction that allows composition of one-time query responses into streams representing sophisticated spatio-temporal phenomena of interest. A distinguishing feature of our middleware is the realization that the suitability of a persistent query's result is a function of the application's tolerance for accuracy weighed against the associated overhead costs. In PAQ, programmers can specify an inquiry strategy that dictates how information is gathered. Since network dynamics impact the suitability of a particular inquiry strategy, PAQ associates an introspection strategy with a persistent query, that evaluates the quality of the query's results. The result of introspection can trigger application-defined adaptation strategies that alter the nature of the query. PAQ's simple API makes developing adaptive querying systems easily realizable. We present the key abstractions, describe their implementations, and demonstrate the middleware's usefulness through application examples and evaluation.

Mobile object retrieval in server-based image databases

Science.gov (United States)

Manger, D.; Pagel, F.; Widak, H.

2013-05-01

The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.

EquiX-A Search and Query Language for XML.

Science.gov (United States)

Cohen, Sara; Kanza, Yaron; Kogan, Yakov; Sagiv, Yehoshua; Nutt, Werner; Serebrenik, Alexander

2002-01-01

Describes EquiX, a search language for XML that combines querying with searching to query the data and the meta-data content of Web pages. Topics include search engines; a data model for XML documents; search query syntax; search query semantics; an algorithm for evaluating a query on a document; and indexing EquiX queries. (LRW)

QUERY RESPONSE TIME COMPARISON NOSQLDB MONGODB WITH SQLDB ORACLE

Directory of Open Access Journals (Sweden)

Humasak T. A. Simanjuntak

2015-01-01

Full Text Available Penyimpanan data saat ini terdapat dua jenis yakni relational database dan non-relational database. Kedua jenis DBMS (Database Managemnet System tersebut berbeda dalam berbagai aspek seperti per-formansi eksekusi query, scalability, reliability maupun struktur penyimpanan data. Kajian ini memiliki tujuan untuk mengetahui perbandingan performansi DBMS antara Oracle sebagai jenis relational data-base dan MongoDB sebagai jenis non-relational database dalam mengolah data terstruktur. Eksperimen dilakukan untuk mengetahui perbandingan performansi kedua DBMS tersebut untuk operasi insert, select, update dan delete dengan menggunakan query sederhana maupun kompleks pada database Northwind. Untuk mencapai tujuan eksperimen, 18 query yang terdiri dari 2 insert query, 10 select query, 2 update query dan 2 delete query dieksekusi. Query dieksekusi melalui sebuah aplikasi .Net yang dibangun sebagai perantara antara user dengan basis data. Eksperimen dilakukan pada tabel dengan atau tanpa relasi pada Oracle dan embedded atau bukan embedded dokumen pada MongoDB. Response time untuk setiap eksekusi query dibandingkan dengan menggunakan metode statistik. Eksperimen menunjukkan response time query untuk proses select, insert, dan update pada MongoDB lebih cepatdaripada Oracle. MongoDB lebih cepat 64.8 % untuk select query;MongoDB lebihcepat 72.8 % untuk insert query dan MongoDB lebih cepat 33.9 % untuk update query. Pada delete query, Oracle lebih cepat 96.8 % daripada MongoDB untuk table yang berelasi, tetapi MongoDB lebih cepat 83.8 % daripada Oracle untuk table yang tidak memiliki relasi.Untuk query kompleks dengan Map Reduce pada MongoDB lebih lambat 97.6% daripada kompleks query dengan aggregate function pada Oracle.

Learning jQuery

CERN Document Server

Chaffer, Jonathan

2013-01-01

Step through each of the core concepts of the jQuery library, building an overall picture of its capabilities. Once you have thoroughly covered the basics, the book returns to each concept to cover more advanced examples and techniques.This book is for web designers who want to create interactive elements for their designs, and for developers who want to create the best user interface for their web applications. Basic JavaScript programming and knowledge of HTML and CSS is required. No knowledge of jQuery is assumed, nor is experience with any other JavaScript libraries.

Knowledge Query Language (KQL)

Science.gov (United States)

2016-02-12

described as a sparse, distributed multidimensional sorted map. Unlike a relational database , BigTable has no multicolumn primary keys or constraints. The...in query languages such as SQL. Figure 3. Address expression-based querying. Each circled step in Figure 3 is described below. Datastore/ Database ...implementation we describe in later sections stores the instance of registry ontology in JSON files. 7 Throughout the rest of this report, we use the

The role of retrieval mode and retrieval orientation in retrieval practice: insights from comparing recognition memory testing formats and restudying.

Science.gov (United States)

Gao, Chuanji; Rosburg, Timm; Hou, Mingzhu; Li, Bingbing; Xiao, Xin; Guo, Chunyan

2016-12-01

The effectiveness of retrieval practice for aiding long-term memory, referred to as the testing effect, has been widely demonstrated. However, the specific neurocognitive mechanisms underlying this phenomenon remain unclear. In the present study, we sought to explore the role of pre-retrieval processes at initial testing on later recognition performance by using event-related potentials (ERPs). Subjects studied two lists of words (Chinese characters) and then performed a recognition task or a source memory task, or restudied the word lists. At the end of the experiment, subjects received a final recognition test based on the remember-know paradigm. Behaviorally, initial testing (active retrieval) enhanced memory retention relative to restudying (passive retrieval). The retrieval mode at initial testing was indexed by more positive-going ERPs for unstudied items in the active-retrieval tasks than in passive retrieval from 300 to 900 ms. Follow-up analyses showed that the magnitude of the early ERP retrieval mode effect (300-500 ms) was predictive of the behavioral testing effect later on. In addition, the ERPs for correctly rejected new items during initial testing differed between the two active-retrieval tasks from 500 to 900 ms, and this ERP retrieval orientation effect predicted differential behavioral testing gains between the two active-retrieval conditions. Our findings confirm that initial testing promotes later retrieval relative to restudying, and they further suggest that adopting pre-retrieval processing in the forms of retrieval mode and retrieval orientation might contribute to these memory enhancements.

Enhancing Recall in Semantic Querying

DEFF Research Database (Denmark)

Rouces, Jacobo

2013-01-01

lexically and structurally different, which we will introduce in the next section. As RDF graphs from different sources are expected to be linked, the modeling heterogeneities will make the federated graph become sparser and inconsistent. This is detrimental to the recall of SPARQL queries, as the query...

Effects of Individualized Word Retrieval in Kindergarten Vocabulary Intervention

Science.gov (United States)

Damhuis, Carmen M. P.; Segers, Eliane; Scheltinga, Femke; Verhoeven, Ludo

2016-01-01

We examined the effects of adaptive word retrieval intervention on a classroom vocabulary program on children's vocabulary acquisition in kindergarten. In the experimental condition, word retrieval was provided in a classroom vocabulary program, combining implicit and explicit vocabulary instructions. Children performed extra word retrieval…

Modeling and mining term association for improving biomedical information retrieval performance.

Science.gov (United States)

Hu, Qinmin; Huang, Jimmy Xiangji; Hu, Xiaohua

2012-06-11

The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent

Location-Dependent Query Processing Under Soft Real-Time Constraints

Directory of Open Access Journals (Sweden)

Zoubir Mammeri

2009-01-01

Full Text Available In recent years, mobile devices and applications achieved an increasing development. In database field, this development required methods to consider new query types like location-dependent queries (i.e. the query results depend on the query issuer location. Although several researches addressed problems related to location-dependent query processing, a few works considered timing requirements that may be associated with queries (i.e., the query results must be delivered to mobile clients on time. The main objective of this paper is to propose a solution for location-dependent query processing under soft real-time constraints. Hence, we propose methods to take into account client location-dependency and to maximize the percentage of queries respecting their deadlines. We validate our proposal by implementing a prototype based on Oracle DBMS. Performance evaluation results show that the proposed solution optimizes the percentage of queries meeting their deadlines and the communication cost.

SCRY: Enabling quantitative reasoning in SPARQL queries

NARCIS (Netherlands)

Meroño-Peñuela, A.; Stringer, Bas; Loizou, Antonis; Abeln, Sanne; Heringa, Jaap

2015-01-01

The inability to include quantitative reasoning in SPARQL queries slows down the application of Semantic Web technology in the life sciences. SCRY, our SPARQL compatible service layer, improves this by executing services at query time and making their outputs query-accessible, generating RDF data on

Seasonal trends in hypertension in Poland: evidence from Google search engine query data.

Science.gov (United States)

Płatek, Anna E; Sierdziński, Janusz; Krzowski, Bartosz; Szymański, Filip M

2018-01-01

Various conditions, including arterial hypertension, exhibit seasonal trends in their occurrence and magnitude. Those trends correspond to an interest exhibited in the number of Internet searches for the specific conditions per month. The aim of the study was to show seasonal trends in the hypertension prevalence in Poland relate to the data from the Google Trends tool. Internet search engine query data were retrieved from Google Trends from January 2008 to November 2017. Data were calculated as a monthly normalised search volume from the nine-year period. Data was presented for specific geographic regions, including Poland, the United States of America, Australia, and worldwide for the following search terms: "arterial hypertension (pol. nadciśnienie tętnicze)", "hypertension (pol. nadciśnienie)" and "hypertension medical condition". Seasonal effects were calculated using regression models and presented graphically. In Poland the search volume is the highest between November and May, while patients exhibit the least interest in arterial hypertension during summer holidays (p Google.

Answering SPARQL queries modulo RDF Schema with paths

OpenAIRE

Alkhateeb, Faisal; Euzenat, Jérôme

2013-01-01

alkhateeb2013a; SPARQL is the standard query language for RDF graphs. In its strict instantiation, it only offers querying according to the RDF semantics and would thus ignore the semantics of data expressed with respect to (RDF) schemas or (OWL) ontologies. Several extensions to SPARQL have been proposed to query RDF data modulo RDFS, i.e., interpreting the query with RDFS semantics and/or considering external ontologies. We introduce a general framework which allows for expressing query ans...

Implementation of Quantum Private Queries Using Nuclear Magnetic Resonance

International Nuclear Information System (INIS)

Wang Chuan; Hao Liang; Zhao Lian-Jie

2011-01-01

We present a modified protocol for the realization of a quantum private query process on a classical database. Using one-qubit query and CNOT operation, the query process can be realized in a two-mode database. In the query process, the data privacy is preserved as the sender would not reveal any information about the database besides her query information, and the database provider cannot retain any information about the query. We implement the quantum private query protocol in a nuclear magnetic resonance system. The density matrix of the memory registers are constructed. (general)

When Does Retrieval Induce Forgetting and when Does It Induce Facilitation? Implications for Retrieval Inhibition, Testing Effect, and Text Processing

Science.gov (United States)

Chan, Jason C. K.

2009-01-01

Retrieval practice can enhance long-term retention of the tested material (the testing effect), but it can also impair later recall of the nontested material--a phenomenon known as retrieval-induced forgetting (Anderson, M. C., Bjork, R. A., & Bjork, E. L. (1994). "Remembering can cause forgetting: retrieval dynamics in long-term memory." "Journal…

Mobile Information Access with Spoken Query Answering

DEFF Research Database (Denmark)

Brøndsted, Tom; Larsen, Henrik Legind; Larsen, Lars Bo

2006-01-01

window focused over the part which most likely contains an answer to the query. The two systems are integrated into a full spoken query answering system. The prototype can answer queries and questions within the chosen football (soccer) test domain, but the system has the flexibility for being ported...

On the formulation of performant sparql queries

NARCIS (Netherlands)

Loizou, A.; Angles, R.; Groth, P.T.

2014-01-01

Abstract The combination of the flexibility of RDF and the expressiveness of SPARQL provides a powerful mechanism to model, integrate and query data. However, these properties also mean that it is nontrivial to write performant SPARQL queries. Indeed, it is quite easy to create queries that tax even

The Pretesting Effect: Do Unsuccessful Retrieval Attempts Enhance Learning?

Science.gov (United States)

Richland, Lindsey E.; Kornell, Nate; Kao, Liche Sean

2009-01-01

Testing previously studied information enhances long-term memory, particularly when the information is successfully retrieved from memory. The authors examined the effect of unsuccessful retrieval attempts on learning. Participants in 5 experiments read an essay about vision. In the test condition, they were asked about embedded concepts before…

An Information Retrieval and Recommendation System for Astronomical Observatories

Science.gov (United States)

Mukund, Nikhil; Thakur, Saurabh; Abraham, Sheelu; Aniyan, A. K.; Mitra, Sanjit; Sajeeth Philip, Ninan; Vaghmare, Kaustubh; Acharjya, D. P.

2018-03-01

We present a machine-learning-based information retrieval system for astronomical observatories that tries to address user-defined queries related to an instrument. In the modern instrumentation scenario where heterogeneous systems and talents are simultaneously at work, the ability to supply people with the right information helps speed up the tasks for detector operation, maintenance, and upgradation. The proposed method analyzes existing documented efforts at the site to intelligently group related information to a query and to present it online to the user. The user in response can probe the suggested content and explore previously developed solutions or probable ways to address the present situation optimally. We demonstrate natural language-processing-backed knowledge rediscovery by making use of the open source logbook data from the Laser Interferometric Gravitational Observatory (LIGO). We implement and test a web application that incorporates the above idea for LIGO Livingston, LIGO Hanford, and Virgo observatories.

Evolutionary Multiobjective Query Workload Optimization of Cloud Data Warehouses

Science.gov (United States)

Dokeroglu, Tansel; Sert, Seyyit Alper; Cinar, Muhammet Serkan

2014-01-01

With the advent of Cloud databases, query optimizers need to find paretooptimal solutions in terms of response time and monetary cost. Our novel approach minimizes both objectives by deploying alternative virtual resources and query plans making use of the virtual resource elasticity of the Cloud. We propose an exact multiobjective branch-and-bound and a robust multiobjective genetic algorithm for the optimization of distributed data warehouse query workloads on the Cloud. In order to investigate the effectiveness of our approach, we incorporate the devised algorithms into a prototype system. Finally, through several experiments that we have conducted with different workloads and virtual resource configurations, we conclude remarkable findings of alternative deployments as well as the advantages and disadvantages of the multiobjective algorithms we propose. PMID:24892048

Responsive web design with jQuery

CERN Document Server

Carlos, Gilberto

2013-01-01

Responsive Web Design with jQuery follows a standard tutorial-based approach, covering various aspects of responsive web design by building a comprehensive website.""Responsive Web Design with jQuery"" is aimed at web designers who are interested in building device-agnostic websites. You should have a grasp of standard HTML, CSS, and JavaScript development, and have a familiarity with graphic design. Some exposure to jQuery and HTML5 will be beneficial but isn't essential.

Adding query privacy to robust DHTs

DEFF Research Database (Denmark)

Backes, Michael; Goldberg, Ian; Kate, Aniket

2012-01-01

intermediate peers that (help to) route the queries towards their destinations. In this paper, we satisfy this requirement by presenting an approach for providing privacy for the keys in DHT queries. We use the concept of oblivious transfer (OT) in communication over DHTs to preserve query privacy without...... privacy over robust DHTs. Finally, we compare the performance of our privacy-preserving protocols with their more privacy-invasive counterparts. We observe that there is no increase in the message complexity...

Learning binary code via PCA of angle projection for image retrieval

Science.gov (United States)

Yang, Fumeng; Ye, Zhiqiang; Wei, Xueqi; Wu, Congzhong

2018-01-01

With benefits of low storage costs and high query speeds, binary code representation methods are widely researched for efficiently retrieving large-scale data. In image hashing method, learning hashing function to embed highdimensions feature to Hamming space is a key step for accuracy retrieval. Principal component analysis (PCA) technical is widely used in compact hashing methods, and most these hashing methods adopt PCA projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit by thresholding. The variances of different projected dimensions are different, and with real-valued projection produced more quantization error. To avoid the real-valued projection with large quantization error, in this paper we proposed to use Cosine similarity projection for each dimensions, the angle projection can keep the original structure and more compact with the Cosine-valued. We used our method combined the ITQ hashing algorithm, and the extensive experiments on the public CIFAR-10 and Caltech-256 datasets validate the effectiveness of the proposed method.

SPARQL Assist language-neutral query composer

Science.gov (United States)

2012-01-01

Background SPARQL query composition is difficult for the lay-person, and even the experienced bioinformatician in cases where the data model is unfamiliar. Moreover, established best-practices and internationalization concerns dictate that the identifiers for ontological terms should be opaque rather than human-readable, which further complicates the task of synthesizing queries manually. Results We present SPARQL Assist: a Web application that addresses these issues by providing context-sensitive type-ahead completion during SPARQL query construction. Ontological terms are suggested using their multi-lingual labels and descriptions, leveraging existing support for internationalization and language-neutrality. Moreover, the system utilizes the semantics embedded in ontologies, and within the query itself, to help prioritize the most likely suggestions. Conclusions To ensure success, the Semantic Web must be easily available to all users, regardless of locale, training, or preferred language. By enhancing support for internationalization, and moreover by simplifying the manual construction of SPARQL queries through the use of controlled-natural-language interfaces, we believe we have made some early steps towards simplifying access to Semantic Web resources. PMID:22373327

SPARQL assist language-neutral query composer.

Science.gov (United States)

McCarthy, Luke; Vandervalk, Ben; Wilkinson, Mark

2012-01-25

SPARQL query composition is difficult for the lay-person, and even the experienced bioinformatician in cases where the data model is unfamiliar. Moreover, established best-practices and internationalization concerns dictate that the identifiers for ontological terms should be opaque rather than human-readable, which further complicates the task of synthesizing queries manually. We present SPARQL Assist: a Web application that addresses these issues by providing context-sensitive type-ahead completion during SPARQL query construction. Ontological terms are suggested using their multi-lingual labels and descriptions, leveraging existing support for internationalization and language-neutrality. Moreover, the system utilizes the semantics embedded in ontologies, and within the query itself, to help prioritize the most likely suggestions. To ensure success, the Semantic Web must be easily available to all users, regardless of locale, training, or preferred language. By enhancing support for internationalization, and moreover by simplifying the manual construction of SPARQL queries through the use of controlled-natural-language interfaces, we believe we have made some early steps towards simplifying access to Semantic Web resources.

EFFECTIVELY SEARCHING SPECIMEN AND OBSERVATION DATA WITH TOQE, THE THESAURUS OPTIMIZED QUERY EXPANDER

Directory of Open Access Journals (Sweden)

Anton Güntsch

2009-09-01

Full Text Available Today’s specimen and observation data portals lack a flexible mechanism, able to link up thesaurus-enabled data sources such as taxonomic checklist databases and expand user queries to related terms, significantly enhancing result sets. The TOQE system (Thesaurus Optimized Query Expander is a REST-like XML web-service implemented in Python and designed for this purpose. Acting as an interface between portals and thesauri, TOQE allows the implementation of specialized portal systems with a set of thesauri supporting its specific focus. It is both easy to use for portal programmers and easy to configure for thesaurus database holders who want to expose their system as a service for query expansions. Currently, TOQE is used in four specimen and observation data portals. The documentation is available from http://search.biocase.org/toqe/.

Query Optimizations over Decentralized RDF Graphs

KAUST Repository

Abdelaziz, Ibrahim; Mansour, Essam; Ouzzani, Mourad; Aboulnaga, Ashraf; Kalnis, Panos

2017-01-01

Applications in life sciences, decentralized social networks, Internet of Things, and statistical linked dataspaces integrate data from multiple decentralized RDF graphs via SPARQL queries. Several approaches have been proposed to optimize query

A new method for the automatic retrieval of medical cases based on the RadLex ontology.

Science.gov (United States)

Spanier, A B; Cohen, D; Joskowicz, L

2017-03-01

The goal of medical case-based image retrieval (M-CBIR) is to assist radiologists in the clinical decision-making process by finding medical cases in large archives that most resemble a given case. Cases are described by radiology reports comprised of radiological images and textual information on the anatomy and pathology findings. The textual information, when available in standardized terminology, e.g., the RadLex ontology, and used in conjunction with the radiological images, provides a substantial advantage for M-CBIR systems. We present a new method for incorporating textual radiological findings from medical case reports in M-CBIR. The input is a database of medical cases, a query case, and the number of desired relevant cases. The output is an ordered list of the most relevant cases in the database. The method is based on a new case formulation, the Augmented RadLex Graph and an Anatomy-Pathology List. It uses a new case relatedness metric [Formula: see text] that prioritizes more specific medical terms in the RadLex tree over less specific ones and that incorporates the length of the query case. An experimental study on 8 CT queries from the 2015 VISCERAL 3D Case Retrieval Challenge database consisting of 1497 volumetric CT scans shows that our method has accuracy rates of 82 and 70% on the first 10 and 30 most relevant cases, respectively, thereby outperforming six other methods. The increasing amount of medical imaging data acquired in clinical practice constitutes a vast database of untapped diagnostically relevant information. This paper presents a new hybrid approach to retrieving the most relevant medical cases based on textual and image information.

Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects

DEFF Research Database (Denmark)

Cong, Gao; Jensen, Christian Søndergaard; Wu, Dingming

2009-01-01

The conventional Internet is acquiring a geo-spatial dimension. Web documents are being geo-tagged, and geo-referenced objects such as points of interest are being associated with descriptive text documents. The resulting fusion of geo-location and documents enables a new kind of top-k query...... that takes into account both location proximity and text relevancy. To our knowledge, only naive techniques exist that are capable of computing a general web information retrieval query while also taking location into account. This paper proposes a new indexing framework for location-aware top-k text...... both text relevancy and location proximity to prune the search space. Results of empirical studies with an implementation of the framework demonstrate that the paper’s proposal offers scalability and is capable of excellent performance....

PERANGKAT BANTU UNTUK OPTIMASI QUERY PADA ORACLE DENGAN RESTRUKTURISASI SQL

Directory of Open Access Journals (Sweden)

Darlis Heru Murti

2006-07-01

Full Text Available Query merupakan bagian dari bahasa pemrograman SQL (Structured Query Language yang berfungsi untuk mengambil data (read dalam DBMS (Database Management System, termasuk Oracle [3]. Pada Oracle, ada tiga tahap proses yang dilakukan dalam pengeksekusian query, yaitu Parsing, Execute dan Fetch. Sebelum proses execute dijalankan, Oracle terlebih dahulu membuat execution plan yang akan menjadi skenario dalam proses excute.Dalam proses pengeksekusian query, terdapat faktor-faktor yang mempengaruhi kinerja query, di antaranya access path (cara pengambilan data dari sebuah tabel dan operasi join (cara menggabungkan data dari dua tabel. Untuk mendapatkan query dengan kinerja optimal, maka diperlukan pertimbangan-pertimbangan dalam menyikapi faktor-faktor tersebut.  Optimasi query merupakan suatu cara untuk mendapatkan query dengan kinerja seoptimal mungkin, terutama dilihat dari sudut pandang waktu. Ada banyak metode untuk mengoptimasi query, tapi pada Penelitian ini, penulis membuat sebuah aplikasi untuk mengoptimasi query dengan metode restrukturisasi SQL statement. Pada metode ini, objek yang dianalisa adalah struktur klausa yang membangun sebuah query. Aplikasi ini memiliki satu input dan lima jenis output. Input dari aplikasi ini adalah sebuah query sedangkan kelima jenis output aplikasi ini adalah berupa query hasil optimasi, saran perbaikan, saran pembuatan indeks baru, execution plan dan data statistik. Cara kerja aplikasi ini dibagi menjadi empat tahap yaitu mengurai query menjadi sub query, mengurai query per-klausa, menentukan access path dan operasi join dan restrukturisasi query.Dari serangkaian ujicoba yang dilakukan penulis, aplikasi telah dapat berjalan sesuai dengan tujuan pembuatan Penelitian ini, yaitu mendapatkan query dengan kinerja optimal.Kata Kunci : Query, SQL, DBMS, Oracle, Parsing, Execute, Fetch, Execution Plan, Access Path, Operasi Join, Restrukturisasi SQL statement.

Evaluating SPARQL queries on massive RDF datasets

KAUST Repository

Al-Harbi, Razen; Abdelaziz, Ibrahim; Kalnis, Panos; Mamoulis, Nikos

2015-01-01

In this paper, we propose AdHash, a distributed RDF system which addresses the shortcomings of previous work. First, AdHash initially applies lightweight hash partitioning, which drastically minimizes the startup cost, while favoring the parallel processing of join patterns on subjects, without any data communication. Using a locality-aware planner, queries that cannot be processed in parallel are evaluated with minimal communication. Second, AdHash monitors the data access patterns and adapts dynamically to the query load by incrementally redistributing and replicating frequently accessed data. As a result, the communication cost for future queries is drastically reduced or even eliminated. Our experiments with synthetic and real data verify that AdHash (i) starts faster than all existing systems, (ii) processes thousands of queries before other systems become online, and (iii) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in sub-seconds. In this demonstration, audience can use a graphical interface of AdHash to verify its performance superiority compared to state-of-the-art distributed RDF systems.

Design and analysis of stochastic DSS query optimizers in a distributed database system

Directory of Open Access Journals (Sweden)

Manik Sharma

2016-07-01

Full Text Available Query optimization is a stimulating task of any database system. A number of heuristics have been applied in recent times, which proposed new algorithms for substantially improving the performance of a query. The hunt for a better solution still continues. The imperishable developments in the field of Decision Support System (DSS databases are presenting data at an exceptional rate. The massive volume of DSS data is consequential only when it is able to access and analyze by distinctive researchers. Here, an innovative stochastic framework of DSS query optimizer is proposed to further optimize the design of existing query optimization genetic approaches. The results of Entropy Based Restricted Stochastic Query Optimizer (ERSQO are compared with the results of Exhaustive Enumeration Query Optimizer (EAQO, Simple Genetic Query Optimizer (SGQO, Novel Genetic Query Optimizer (NGQO and Restricted Stochastic Query Optimizer (RSQO. In terms of Total Costs, EAQO outperforms SGQO, NGQO, RSQO and ERSQO. However, stochastic approaches dominate in terms of runtime. The Total Costs produced by ERSQO is better than SGQO, NGQO and RGQO by 12%, 8% and 5% respectively. Moreover, the effect of replicating data on the Total Costs of DSS query is also examined. In addition, the statistical analysis revealed a 2-tailed significant correlation between the number of join operations and the Total Costs of distributed DSS query. Finally, in regard to the consistency of stochastic query optimizers, the results of SGQO, NGQO, RSQO and ERSQO are 96.2%, 97.2%, 97.45 and 97.8% consistent respectively.

Retrieval of bilingual autobiographical memories: effects of cue language and cue imageability.

Science.gov (United States)

Mortensen, Linda; Berntsen, Dorthe; Bohn, Ocke-Schwen

2015-01-01

An important issue in theories of bilingual autobiographical memory is whether linguistically encoded memories are represented in language-specific stores or in a common language-independent store. Previous research has found that autobiographical memory retrieval is facilitated when the language of the cue is the same as the language of encoding, consistent with language-specific memory stores. The present study examined whether this language congruency effect is influenced by cue imageability. Danish-English bilinguals retrieved autobiographical memories in response to Danish and English high- or low-imageability cues. Retrieval latencies were shorter to Danish than English cues and shorter to high- than low-imageability cues. Importantly, the cue language effect was stronger for low-than high-imageability cues. To examine the relationship between cue language and the language of internal retrieval, participants identified the language in which the memories were internally retrieved. More memories were retrieved when the cue language was the same as the internal language than when the cue was in the other language, and more memories were identified as being internally retrieved in Danish than English, regardless of the cue language. These results provide further evidence for language congruency effects in bilingual memory and suggest that this effect is influenced by cue imageability.

Evaluating SPARQL queries on massive RDF datasets

KAUST Repository

Al-Harbi, Razen

2015-08-01

Distributed RDF systems partition data across multiple computer nodes. Partitioning is typically based on heuristics that minimize inter-node communication and it is performed in an initial, data pre-processing phase. Therefore, the resulting partitions are static and do not adapt to changes in the query workload; as a result, existing systems are unable to consistently avoid communication for queries that are not favored by the initial data partitioning. Furthermore, for very large RDF knowledge bases, the partitioning phase becomes prohibitively expensive, leading to high startup costs. In this paper, we propose AdHash, a distributed RDF system which addresses the shortcomings of previous work. First, AdHash initially applies lightweight hash partitioning, which drastically minimizes the startup cost, while favoring the parallel processing of join patterns on subjects, without any data communication. Using a locality-aware planner, queries that cannot be processed in parallel are evaluated with minimal communication. Second, AdHash monitors the data access patterns and adapts dynamically to the query load by incrementally redistributing and replicating frequently accessed data. As a result, the communication cost for future queries is drastically reduced or even eliminated. Our experiments with synthetic and real data verify that AdHash (i) starts faster than all existing systems, (ii) processes thousands of queries before other systems become online, and (iii) gracefully adapts to the query load, being able to evaluate queries on billion-scale RDF data in sub-seconds. In this demonstration, audience can use a graphical interface of AdHash to verify its performance superiority compared to state-of-the-art distributed RDF systems.

Audio Query by Example Using Similarity Measures between Probability Density Functions of Features

Directory of Open Access Journals (Sweden)

Marko Helén

2010-01-01

Full Text Available This paper proposes a query by example system for generic audio. We estimate the similarity of the example signal and the samples in the queried database by calculating the distance between the probability density functions (pdfs of their frame-wise acoustic features. Since the features are continuous valued, we propose to model them using Gaussian mixture models (GMMs or hidden Markov models (HMMs. The models parametrize each sample efficiently and retain sufficient information for similarity measurement. To measure the distance between the models, we apply a novel Euclidean distance, approximations of Kullback-Leibler divergence, and a cross-likelihood ratio test. The performance of the measures was tested in simulations where audio samples are automatically retrieved from a general audio database, based on the estimated similarity to a user-provided example. The simulations show that the distance between probability density functions is an accurate measure for similarity. Measures based on GMMs or HMMs are shown to produce better results than that of the existing methods based on simpler statistics or histograms of the features. A good performance with low computational cost is obtained with the proposed Euclidean distance.

Code query by example