WorldWideScience

Sample records for implicit recommendation system

  1. The Power of Implicit Social Relation in Rating Prediction of Social Recommender Systems.

    Science.gov (United States)

    Reafee, Waleed; Salim, Naomie; Khan, Atif

    2016-01-01

    The explosive growth of social networks in recent times has presented a powerful source of information to be utilized as an extra source for assisting in the social recommendation problems. The social recommendation methods that are based on probabilistic matrix factorization improved the recommendation accuracy and partly solved the cold-start and data sparsity problems. However, these methods only exploited the explicit social relations and almost completely ignored the implicit social relations. In this article, we firstly propose an algorithm to extract the implicit relation in the undirected graphs of social networks by exploiting the link prediction techniques. Furthermore, we propose a new probabilistic matrix factorization method to alleviate the data sparsity problem through incorporating explicit friendship and implicit friendship. We evaluate our proposed approach on two real datasets, Last.Fm and Douban. The experimental results show that our method performs much better than the state-of-the-art approaches, which indicates the importance of incorporating implicit social relations in the recommendation process to address the poor prediction accuracy.

  2. ImWalkMF: Joint matrix factorization and implicit walk integrative learning for recommendation

    KAUST Repository

    Zhang, Chuxu; Yu, Lu; Zhang, Xiangliang; Chawla, Nitesh

    2018-01-01

    Data sparsity and cold-start problems are prevalent in recommender systems. To address such problems, both the observable explicit social information (e.g., user-user trust connections) and the inferable implicit correlations (e.g., implicit

  3. ImWalkMF: Joint matrix factorization and implicit walk integrative learning for recommendation

    KAUST Repository

    Zhang, Chuxu

    2018-01-15

    Data sparsity and cold-start problems are prevalent in recommender systems. To address such problems, both the observable explicit social information (e.g., user-user trust connections) and the inferable implicit correlations (e.g., implicit neighbors computed by similarity measurement) have been introduced to complement user-item ratings data for improving the performances of traditional model-based recommendation algorithms such as matrix factorization. Although effective, (1) the utilization of the explicit user-user social relationships suffers from the weakness of unavailability in real systems such as Netflix or the issue of sparse observable content like 0.03% trust density in Epinions, thus there is no or little explicit social information that can be employed to improve baseline model in real applications; (2) the current similarity measurement approaches focus on inferring implicit correlations between a user (item) and their direct neighbors or top-k similar neighbors based on user-item ratings bipartite network, so that they fail to comprehensively unfold the indirect potential relationships among users and items. To solve these issues regarding both explicit/implicit social recommendation algorithms, we design a joint model of matrix factorization and implicit walk integrative learning, i.e., ImWalkMF, which only uses explicit ratings information yet models both direct rating feedbacks and multiple direct/indirect implicit correlations among users and items from a random walk perspective. We further propose a combined strategy for training two independent components in the proposed model based on sampling. The experimental results on two real-world sparse datasets demonstrate that ImWalkMF outperforms the traditional regularized/probabilistic matrix factorization models as well as other competitive baselines that utilize explicit/implicit social information.

  4. A Hybrid Recommender System Based on User-Recommender Interaction

    OpenAIRE

    Zhang, Heng-Ru; Min, Fan; He, Xu; Xu, Yuan-Yuan

    2015-01-01

    Recommender systems are used to make recommendations about products, information, or services for users. Most existing recommender systems implicitly assume one particular type of user behavior. However, they seldom consider user-recommender interactive scenarios in real-world environments. In this paper, we propose a hybrid recommender system based on user-recommender interaction and evaluate its performance with recall and diversity metrics. First, we define the user-recommender interaction...

  5. DEVELOPMENT OF A GENERIC RECOMMENDER SYSTEM

    Directory of Open Access Journals (Sweden)

    Dan Munteanu

    2004-12-01

    Full Text Available his paper presents a recommender system for textual documents taken from web (given as bookmarks. The system uses for classification a combination of content, event and collaborative filters and for recommendation a modified Pearson-r algorithm. It uses implicit and explicit feedback for evaluating documents.

  6. Implicit Gender Stereotypes and Essentialist Beliefs Predict Preservice Teachers' Tracking Recommendations

    Science.gov (United States)

    Nürnberger, Miriam; Nerb, Josef; Schmitz, Florian; Keller, Johannes; Sütterlin, Stefan

    2016-01-01

    This study investigated the extent to which differences in implicit and explicit math--language gender stereotypes, and essentialist beliefs among preservice teachers affect tracking recommendations for math/science versus language-oriented secondary schools. Consistent with expectations, the results suggest that student's gender influences…

  7. Context-aware recommender system based on ontology for recommending tourist destinations at Bandung

    Science.gov (United States)

    Rizaldy Hafid Arigi, L.; Abdurahman Baizal, Z. K.; Herdiani, Anisa

    2018-03-01

    Recommender System is software that is able to provide personalized recommendation suits users’ needs. Recommender System has been widely implemented in various domains, including tourism. One approach that can be done for more personalized recommendations is the use of contextual information. This paper proposes a context aware recommender based ontology system in the tourism domain. The system is capable of recommending tourist destinations by using user preferences of the categories of tourism and contextual information such as user locations, weather around tourist destinations and close time of destination. Based on the evaluation, the system has accuracy of of 0.94 (item recommendation precision evaluated by expert) and 0.58 (implicitly from system-end user interaction). Based on the evaluation of user satisfaction, the system provides a satisfaction level of more than 0.7 (scale 0 to 1) for speed factors for providing liked recommendations (PE), informative description of recommendations (INF) and user trust (TR).

  8. Archetypal Game Recommender Systems

    DEFF Research Database (Denmark)

    Sifa, Rafet; Bauckhage, C.; Drachen, Anders

    2014-01-01

    Contemporary users (players, consumers) of digital games have thousands of products to choose from, which makes nding games that t their interests challenging. Towards addressing this challenge, in this paper two dierent formulations of Archetypal Analysis for Top-L recommender tasks using implicit...... feedback are presented: factor- and neighborhood-oriented models. These form the rst application of rec- ommender systems to digital games. Both models are tested on a dataset of 500,000 users of the game distribution platform Steam, covering game ownership and playtime data across more than 3000 games....... Compared to four other recommender models (nearest neighbor, two popularity mod- els, random baseline), the archetype based models provide the highest recall rates showing that Archetypal Analysis can be successfully applied for Top-L recommendation purposes...

  9. Classification process in a text document recommender system

    Directory of Open Access Journals (Sweden)

    Dan MUNTEANU

    2005-12-01

    Full Text Available This paper presents the classification process in a recommender system used for textual documents taken especially from web. The system uses in the classification process a combination of content filters, event filters and collaborative filters and it uses implicit and explicit feedback for evaluating documents.

  10. Finding Your Literature Match - A Physics Literature Recommender System

    Science.gov (United States)

    Henneken, Edwin; Kurtz, Michael

    2010-03-01

    A recommender system is a filtering algorithm that helps you find the right match by offering suggestions based on your choices and information you have provided. A latent factor model is a successful approach. Here an item is characterized by a vector describing to what extent a product is described by each of N categories, and a person is characterized by an ``interest'' vector, based on explicit or implicit feedback by this user. The recommender system assigns ratings to new items and suggests items this user might be interested in. Here we present results of a recommender system designed to find recent literature of interest to people working in the field of solid state physics. Since we do not have explicit feedback, our user vector consists of (implicit) ``usage.'' Using a system of N keywords we construct normalized keyword vectors for articles based on the keywords of that article and its bibliography. The normalized ``interest'' vector is created by calculating the normalized frequency of keyword occurrence in the papers cited by the papers read.

  11. The SAPO Campus Recommender System: A Study about Students' and Teachers' Opinions

    Science.gov (United States)

    Pedro, Luís; Santos, Carlos; Almeida, Sara Filipa; Ramos, Fernando; Moreira, António; Almeida, Margarida; Antunes, Maria João

    2014-01-01

    This paper aims to assess the relevance and usefulness of the SAPO Campus recommender system, through the analysis of students' and teachers' opinions. Recommender systems, assuming a "technology-driven" approach, have been designed with the primary goal of predicting user interests based on the implicit analysis of their actions and…

  12. Models and methods for building web recommendation systems

    OpenAIRE

    Stekh, Yu.; Artsibasov, V.

    2012-01-01

    Modern Word Wide Web contains a large number of Web sites and pages in each Web site. Web recommendation system (recommendation system for web pages) are typically implemented on web servers and use the data obtained from the collection viewed web templates (implicit data) or user registration data (explicit data). In article considering methods and algorithms of web recommendation system based on the technology of data mining (web mining). Сучасна мережа Інтернет містить велику кількість веб...

  13. Hybrid attribute-based recommender system for learning material using genetic algorithm and a multidimensional information model

    Directory of Open Access Journals (Sweden)

    Mojtaba Salehi

    2013-03-01

    Full Text Available In recent years, the explosion of learning materials in the web-based educational systems has caused difficulty of locating appropriate learning materials to learners. A personalized recommendation is an enabling mechanism to overcome information overload occurred in the new learning environments and deliver suitable materials to learners. Since users express their opinions based on some specific attributes of items, this paper proposes a hybrid recommender system for learning materials based on their attributes to improve the accuracy and quality of recommendation. The presented system has two main modules: explicit attribute-based recommender and implicit attribute-based recommender. In the first module, weights of implicit or latent attributes of materials for learner are considered as chromosomes in genetic algorithm then this algorithm optimizes the weights according to historical rating. Then, recommendation is generated by Nearest Neighborhood Algorithm (NNA using the optimized weight vectors implicit attributes that represent the opinions of learners. In the second, preference matrix (PM is introduced that can model the interests of learner based on explicit attributes of learning materials in a multidimensional information model. Then, a new similarity measure between PMs is introduced and recommendations are generated by NNA. The experimental results show that our proposed method outperforms current algorithms on accuracy measures and can alleviate some problems such as cold-start and sparsity.

  14. Using the Context of User Feedback in Recommender Systems

    Directory of Open Access Journals (Sweden)

    Ladislav Peska

    2016-12-01

    Full Text Available Our work is generally focused on recommending for small or medium-sized e-commerce portals, where explicit feedback is absent and thus the usage of implicit feedback is necessary. Nonetheless, for some implicit feedback features, the presentation context may be of high importance. In this paper, we present a model of relevant contextual features affecting user feedback, propose methods leveraging those features, publish a dataset of real e-commerce users containing multiple user feedback indicators as well as its context and finally present results of purchase prediction and recommendation experiments. Off-line experiments with real users of a Czech travel agency website corroborated the importance of leveraging presentation context in both purchase prediction and recommendation tasks.

  15. Decision-Guided Recommenders with Composite Alternatives

    Science.gov (United States)

    Alodhaibi, Khalid

    2011-01-01

    Recommender systems aim to support users in their decision-making process while interacting with large information spaces and recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems are increasingly used with product and service selection over the Internet. Although…

  16. Report on RecSys 2016 Workshop on New Trends in Content-Based Recommender Systems

    DEFF Research Database (Denmark)

    Bogers, Toine; Koolen, Marijn; Musto, Cataldo

    2017-01-01

    This article reports on the CBRecSys 2016 workshop, the third edition of the workshop on New Trends in Content-based Recommender Systems, co-located with RecSys 2016 in Boston, MA. Content-based recommendation has been applied successfully in many different domains, but it has not seen the same...... for work dedicated to all aspects of content-based recommender systems....... level of attention as collaborative filtering techniques have. Nevertheless, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. The CBRecSys workshop series provides a dedicated venue...

  17. Fuzzy prototype classifier based on items and its application in recommender system

    Directory of Open Access Journals (Sweden)

    Mei Cai

    2017-01-01

    Full Text Available Currently, recommender systems (RS are incorporating implicit information from social circle of the Internet. The implicit social information in human mind is not easy to reflect in appropriate decision making techniques. This paper consists of 2 contributions. First, we develop an item-based prototype classifier (IPC in which a prototype represents a social circlers preferences as a pattern classification technique. We assume the social circle which distinguishes with others by the items their members like. The prototype structure of the classifier is defined by two2-dimensional matrices. We use information gain and OWA aggregator to construct a feature space. The item-based classifier assigns a new item to some prototypes with different prototypicalities. We reform a typical data setmIris data set in UCI Machine Learning Repository to verify our fuzzy prototype classifier. The second proposition of this paper is to give the application of IPC in recommender system to solve new item cold-start problems. We modify the dataset of MovieLens to perform experimental demonstrations of the proposed ideas.

  18. Primary motor and premotor cortex in implicit sequence learning--evidence for competition between implicit and explicit human motor memory systems.

    Science.gov (United States)

    Kantak, Shailesh S; Mummidisetty, Chaithanya K; Stinear, James W

    2012-09-01

    Implicit and explicit memory systems for motor skills compete with each other during and after motor practice. Primary motor cortex (M1) is known to be engaged during implicit motor learning, while dorsal premotor cortex (PMd) is critical for explicit learning. To elucidate the neural substrates underlying the interaction between implicit and explicit memory systems, adults underwent a randomized crossover experiment of anodal transcranial direct current stimulation (AtDCS) applied over M1, PMd or sham stimulation during implicit motor sequence (serial reaction time task, SRTT) practice. We hypothesized that M1-AtDCS during practice will enhance online performance and offline learning of the implicit motor sequence. In contrast, we also hypothesized that PMd-AtDCS will attenuate performance and retention of the implicit motor sequence. Implicit sequence performance was assessed at baseline, at the end of acquisition (EoA), and 24 h after practice (retention test, RET). M1-AtDCS during practice significantly improved practice performance and supported offline stabilization compared with Sham tDCS. Performance change from EoA to RET revealed that PMd-AtDCS during practice attenuated offline stabilization compared with M1-AtDCS and sham stimulation. The results support the role of M1 in implementing online performance gains and offline stabilization for implicit motor sequence learning. In contrast, enhancing the activity within explicit motor memory network nodes such as the PMd during practice may be detrimental to offline stabilization of the learned implicit motor sequence. These results support the notion of competition between implicit and explicit motor memory systems and identify underlying neural substrates that are engaged in this competition. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  19. TRSDL: Tag-Aware Recommender System Based on Deep Learning–Intelligent Computing Systems

    Directory of Open Access Journals (Sweden)

    Nan Liang

    2018-05-01

    Full Text Available In recommender systems (RS, many models are designed to predict ratings of items for the target user. To improve the performance for rating prediction, some studies have introduced tags into recommender systems. Tags benefit RS considerably, however, they are also redundant and ambiguous. In this paper, we propose a hybrid deep learning model TRSDL (tag-aware recommender system based on deep learning to improve the performance of tag-aware recommender systems (TRS. First, TRSDL uses pre-trained word embeddings to represent user-defined tags, and constructs item and user profiles based on the items’ tags set and users’ tagging behaviors. Then, it utilizes deep neural networks (DNNs and recurrent neural networks (RNNs to extract the latent features of items and users, respectively. Finally, it predicts ratings from these latent features. The model not only addresses tag limitations and takes advantage of semantic tag information but also learns more advanced implicit features via deep structures. We evaluated our proposed approach and several baselines on MovieLens-20 m, and the experimental results demonstrate that TRSDL significantly outperforms all the baselines (including the state-of-the-art models BiasedMF and I-AutoRec. In addition, we also explore the impacts of network depth and type on model performance.

  20. Modular implicits

    Directory of Open Access Journals (Sweden)

    Leo White

    2015-12-01

    Full Text Available We present modular implicits, an extension to the OCaml language for ad-hoc polymorphism inspired by Scala implicits and modular type classes. Modular implicits are based on type-directed implicit module parameters, and elaborate straightforwardly into OCaml's first-class functors. Basing the design on OCaml's modules leads to a system that naturally supports many features from other languages with systematic ad-hoc overloading, including inheritance, instance constraints, constructor classes and associated types.

  1. Report on RecSys 2015 Workshop on New Trends in Content-Based Recommender Systems (CBRecSys 2015)

    DEFF Research Database (Denmark)

    Bogers, Toine; Koolen, Marijn

    2016-01-01

    This article reports on the CBRecSys 2015 workshop, the second edition of the workshop on new trends in content-based recommender systems, co-located with RecSys 2015 in Vienna, Austria. Content-based recommendation has been applied successfully in many different domains, but it has not seen...... venue for work dedicated to all aspects of content-based recommender systems....... the same level of attention as collaborative filtering techniques have. Nevertheless, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. The CBRecSys workshop series provides a dedicated...

  2. Collaborative User Network Embedding for Social Recommender Systems

    KAUST Repository

    Zhang, Chuxu

    2017-06-09

    To address the issue of data sparsity and cold-start in recommender system, social information (e.g., user-user trust links) has been introduced to complement rating data for improving the performances of traditional model-based recommendation techniques such as matrix factorization (MF) and Bayesian personalized ranking (BPR). Although effective, the utilization of the explicit user-user relationships extracted directly from such social information has three main limitations. First, it is difficult to obtain explicit and reliable social links. Only a small portion of users indicate explicitly their trusted friends in recommender systems. Second, the “cold-start” users are “cold” not only on rating but also on socializing. There is no significant amount of explicit social information that can be useful for “cold-start” users. Third, an active user can be socially connected with others who have different taste/preference. Direct usage of explicit social links may mislead recommendation. To address these issues, we propose to extract implicit and reliable social information from user feedbacks and identify top-k semantic friends for each user. We incorporate the top-k semantic friends information into MF and BPR frameworks to solve the problems of ratings prediction and items ranking, respectively. The experimental results on three real-world datasets show that our proposed approaches achieve better results than the state-of-the-art MF with explicit social links (with 3.0% improvement on RMSE), and social BPR (with 9.1% improvement on AUC).

  3. Medial temporal lobe involvement in an implicit memory task: evidence of collaborating implicit and explicit memory systems from FMRI and Alzheimer's disease.

    Science.gov (United States)

    Koenig, Phyllis; Smith, Edward E; Troiani, Vanessa; Anderson, Chivon; Moore, Peachie; Grossman, Murray

    2008-12-01

    We used a prototype extraction task to assess implicit learning of a meaningful novel visual category. Cortical activation was monitored in young adults with functional magnetic resonance imaging. We observed occipital deactivation at test consistent with perceptually based implicit learning, and lateral temporal cortex deactivation reflecting implicit acquisition of the category's semantic nature. Medial temporal lobe (MTL) activation during exposure and test suggested involvement of explicit memory as well. Behavioral performance of Alzheimer's disease (AD) patients and healthy seniors was also assessed, and AD performance was correlated with gray matter volume using voxel-based morphometry. AD patients showed learning, consistent with preserved implicit memory, and confirming that AD patients' implicit memory is not limited to abstract patterns. However, patients were somewhat impaired relative to healthy seniors. Occipital and lateral temporal cortical volume correlated with successful AD patient performance, and thus overlapped with young adults' areas of deactivation. Patients' severe MTL atrophy precluded involvement of this region. AD patients thus appear to engage a cortically based implicit memory mechanism, whereas their relative deficit on this task may reflect their MTL disease. These findings suggest that implicit and explicit memory systems collaborate in neurologically intact individuals performing an ostensibly implicit memory task.

  4. ITrace: An implicit trust inference method for trust-aware collaborative filtering

    Science.gov (United States)

    He, Xu; Liu, Bin; Chen, Kejia

    2018-04-01

    The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. A CF algorithm recommends items of interest to the target user by leveraging the votes given by other similar users. In a standard CF framework, it is assumed that the credibility of every voting user is exactly the same with respect to the target user. This assumption is not satisfied and thus may lead to misleading recommendations in many practical applications. A natural countermeasure is to design a trust-aware CF (TaCF) algorithm, which can take account of the difference in the credibilities of the voting users when performing CF. To this end, this paper presents a trust inference approach, which can predict the implicit trust of the target user on every voting user from a sparse explicit trust matrix. Then an improved CF algorithm termed iTrace is proposed, which takes advantage of both the explicit and the predicted implicit trust to provide recommendations with the CF framework. An empirical evaluation on a public dataset demonstrates that the proposed algorithm provides a significant improvement in recommendation quality in terms of mean absolute error.

  5. A second-order iterative implicit-explicit hybrid scheme for hyperbolic systems of conservation laws

    International Nuclear Information System (INIS)

    Dai, Wenlong; Woodward, P.R.

    1996-01-01

    An iterative implicit-explicit hybrid scheme is proposed for hyperbolic systems of conservation laws. Each wave in a system may be implicitly, or explicitly, or partially implicitly and partially explicitly treated depending on its associated Courant number in each numerical cell, and the scheme is able to smoothly switch between implicit and explicit calculations. The scheme is of Godunov-type in both explicit and implicit regimes, is in a strict conservation form, and is accurate to second-order in both space and time for all Courant numbers. The computer code for the scheme is easy to vectorize. Multicolors proposed in this paper may reduce the number of iterations required to reach a converged solution by several orders for a large time step. The feature of the scheme is shown through numerical examples. 38 refs., 12 figs

  6. Modeling stimulus variation in three common implicit attitude tasks.

    Science.gov (United States)

    Wolsiefer, Katie; Westfall, Jacob; Judd, Charles M

    2017-08-01

    We explored the consequences of ignoring the sampling variation due to stimuli in the domain of implicit attitudes. A large literature in psycholinguistics has examined the statistical treatment of random stimulus materials, but the recommendations from this literature have not been applied to the social psychological literature on implicit attitudes. This is partly because of inherent complications in applying crossed random-effect models to some of the most common implicit attitude tasks, and partly because no work to date has demonstrated that random stimulus variation is in fact consequential in implicit attitude measurement. We addressed this problem by laying out statistically appropriate and practically feasible crossed random-effect models for three of the most commonly used implicit attitude measures-the Implicit Association Test, affect misattribution procedure, and evaluative priming task-and then applying these models to large datasets (average N = 3,206) that assess participants' implicit attitudes toward race, politics, and self-esteem. We showed that the test statistics from the traditional analyses are substantially (about 60 %) inflated relative to the more-appropriate analyses that incorporate stimulus variation. Because all three tasks used the same stimulus words and faces, we could also meaningfully compare the relative contributions of stimulus variation across the tasks. In an appendix, we give syntax in R, SAS, and SPSS for fitting the recommended crossed random-effects models to data from all three tasks, as well as instructions on how to structure the data file.

  7. Implicit Particle Filter for Power System State Estimation with Large Scale Renewable Power Integration.

    Science.gov (United States)

    Uzunoglu, B.; Hussaini, Y.

    2017-12-01

    Implicit Particle Filter is a sequential Monte Carlo method for data assimilation that guides the particles to the high-probability by an implicit step . It optimizes a nonlinear cost function which can be inherited from legacy assimilation routines . Dynamic state estimation for almost real-time applications in power systems are becomingly increasingly more important with integration of variable wind and solar power generation. New advanced state estimation tools that will replace the old generation state estimation in addition to having a general framework of complexities should be able to address the legacy software and able to integrate the old software in a mathematical framework while allowing the power industry need for a cautious and evolutionary change in comparison to a complete revolutionary approach while addressing nonlinearity and non-normal behaviour. This work implements implicit particle filter as a state estimation tool for the estimation of the states of a power system and presents the first implicit particle filter application study on a power system state estimation. The implicit particle filter is introduced into power systems and the simulations are presented for a three-node benchmark power system . The performance of the filter on the presented problem is analyzed and the results are presented.

  8. Patients with Parkinson's disease learn to control complex systems-an indication for intact implicit cognitive skill learning.

    Science.gov (United States)

    Witt, Karsten; Daniels, Christine; Daniel, Victoria; Schmitt-Eliassen, Julia; Volkmann, Jens; Deuschl, Günther

    2006-01-01

    Implicit memory and learning mechanisms are composed of multiple processes and systems. Previous studies demonstrated a basal ganglia involvement in purely cognitive tasks that form stimulus response habits by reinforcement learning such as implicit classification learning. We will test the basal ganglia influence on two cognitive implicit tasks previously described by Berry and Broadbent, the sugar production task and the personal interaction task. Furthermore, we will investigate the relationship between certain aspects of an executive dysfunction and implicit learning. To this end, we have tested 22 Parkinsonian patients and 22 age-matched controls on two implicit cognitive tasks, in which participants learned to control a complex system. They interacted with the system by choosing an input value and obtaining an output that was related in a complex manner to the input. The objective was to reach and maintain a specific target value across trials (dynamic system learning). The two tasks followed the same underlying complex rule but had different surface appearances. Subsequently, participants performed an executive test battery including the Stroop test, verbal fluency and the Wisconsin card sorting test (WCST). The results demonstrate intact implicit learning in patients, despite an executive dysfunction in the Parkinsonian group. They lead to the conclusion that the basal ganglia system affected in Parkinson's disease does not contribute to the implicit acquisition of a new cognitive skill. Furthermore, the Parkinsonian patients were able to reach a specific goal in an implicit learning context despite impaired goal directed behaviour in the WCST, a classic test of executive functions. These results demonstrate a functional independence of implicit cognitive skill learning and certain aspects of executive functions.

  9. Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle

    International Nuclear Information System (INIS)

    Lei, Fei; Du, Bin; Liu, Xin; Xie, Xiaoping; Chai, Tian

    2016-01-01

    In this paper, implicit constrained multi-physics model of a motor wheel for an electric vehicle is built and then optimized. A novel optimization approach is proposed to solve the compliance problem between implicit constraints and stochastic global optimization. Firstly, multi-physics model of motor wheel is built from the theories of structural mechanics, electromagnetism and thermal physics. Then, implicit constraints are applied from the vehicle performances and magnetic characteristics. Implicit constrained optimization is carried out by a series of unconstrained optimization and verifications. In practice, sequentially updated subspaces are designed to completely substitute the original design space in local areas. In each subspace, a solution is obtained and is then verified by the implicit constraints. Optimal solutions which satisfy the implicit constraints are accepted as final candidates. The final global optimal solution is optimized from those candidates. Discussions are carried out to discover the differences between optimal solutions with unconstrained problem and different implicit constrained problems. Results show that the implicit constraints have significant influences on the optimal solution and the proposed approach is effective in finding the optimals. - Highlights: • An implicit constrained multi-physics model is built for sizing a motor wheel. • Vehicle dynamic performances are applied as implicit constraints for nonlinear system. • An efficient novel optimization is proposed to explore the constrained design space. • The motor wheel is optimized to achieve maximum efficiency on vehicle dynamics. • Influences of implicit constraints on vehicle performances are compared and analyzed.

  10. Implicit plasma simulation

    International Nuclear Information System (INIS)

    Langdon, A.B.

    1985-01-01

    Implicit time integration methods have been used extensively in numerical modelling of slowly varying phenomena in systems that also support rapid variation. Examples include diffusion, hydrodynamics and reaction kinetics. This article discussed implementation of implicit time integration in plasma codes of the ''particle-in-cell'' family, and the benefits to be gained

  11. Implicit Lagrangian equations and the mathematical modeling of physical systems

    NARCIS (Netherlands)

    Moreau, Luc; van der Schaft, Arjan

    2002-01-01

    We introduce a class of optimal control problems on manifolds which gives rise (via the Pontryagin maximum principle) to a class of implicit Lagrangian systems (a notion which is introduced in the paper). We apply this to the mathematical modeling of interconnected mechanical systems and mechanical

  12. Modeling single versus multiple systems in implicit and explicit memory.

    Science.gov (United States)

    Starns, Jeffrey J; Ratcliff, Roger; McKoon, Gail

    2012-04-01

    It is currently controversial whether priming on implicit tasks and discrimination on explicit recognition tests are supported by a single memory system or by multiple, independent systems. In a Psychological Review article, Berry and colleagues used mathematical modeling to address this question and provide compelling evidence against the independent-systems approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

  13. Abstract feature codes: The building blocks of the implicit learning system.

    Science.gov (United States)

    Eberhardt, Katharina; Esser, Sarah; Haider, Hilde

    2017-07-01

    According to the Theory of Event Coding (TEC; Hommel, Müsseler, Aschersleben, & Prinz, 2001), action and perception are represented in a shared format in the cognitive system by means of feature codes. In implicit sequence learning research, it is still common to make a conceptual difference between independent motor and perceptual sequences. This supposedly independent learning takes place in encapsulated modules (Keele, Ivry, Mayr, Hazeltine, & Heuer 2003) that process information along single dimensions. These dimensions have remained underspecified so far. It is especially not clear whether stimulus and response characteristics are processed in separate modules. Here, we suggest that feature dimensions as they are described in the TEC should be viewed as the basic content of modules of implicit learning. This means that the modules process all stimulus and response information related to certain feature dimensions of the perceptual environment. In 3 experiments, we investigated by means of a serial reaction time task the nature of the basic units of implicit learning. As a test case, we used stimulus location sequence learning. The results show that a stimulus location sequence and a response location sequence cannot be learned without interference (Experiment 2) unless one of the sequences can be coded via an alternative, nonspatial dimension (Experiment 3). These results support the notion that spatial location is one module of the implicit learning system and, consequently, that there are no separate processing units for stimulus versus response locations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  14. Recommender systems

    OpenAIRE

    Lu L.; Medo M.; Yeung C.H.; Zhang Y.-C.; Zhang Z.-K.; Zhou T.

    2012-01-01

    The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article...

  15. Recommender systems

    CERN Document Server

    Kembellec, Gérald; Saleh, Imad

    2014-01-01

    Acclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understan

  16. Measuring implicit attitudes: A positive framing bias flaw in the Implicit Relational Assessment Procedure (IRAP).

    Science.gov (United States)

    O'Shea, Brian; Watson, Derrick G; Brown, Gordon D A

    2016-02-01

    How can implicit attitudes best be measured? The Implicit Relational Assessment Procedure (IRAP), unlike the Implicit Association Test (IAT), claims to measure absolute, not just relative, implicit attitudes. In the IRAP, participants make congruent (Fat Person-Active: false; Fat Person-Unhealthy: true) or incongruent (Fat Person-Active: true; Fat Person-Unhealthy: false) responses in different blocks of trials. IRAP experiments have reported positive or neutral implicit attitudes (e.g., neutral attitudes toward fat people) in cases in which negative attitudes are normally found on explicit or other implicit measures. It was hypothesized that these results might reflect a positive framing bias (PFB) that occurs when participants complete the IRAP. Implicit attitudes toward categories with varying prior associations (nonwords, social systems, flowers and insects, thin and fat people) were measured. Three conditions (standard, positive framing, and negative framing) were used to measure whether framing influenced estimates of implicit attitudes. It was found that IRAP scores were influenced by how the task was framed to the participants, that the framing effect was modulated by the strength of prior stimulus associations, and that a default PFB led to an overestimation of positive implicit attitudes when measured by the IRAP. Overall, the findings question the validity of the IRAP as a tool for the measurement of absolute implicit attitudes. A new tool (Simple Implicit Procedure:SIP) for measuring absolute, not just relative, implicit attitudes is proposed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  17. Implicit finite-difference simulations of seismic wave propagation

    KAUST Repository

    Chu, Chunlei; Stoffa, Paul L.

    2012-01-01

    We propose a new finite-difference modeling method, implicit both in space and in time, for the scalar wave equation. We use a three-level implicit splitting time integration method for the temporal derivative and implicit finite-difference operators of arbitrary order for the spatial derivatives. Both the implicit splitting time integration method and the implicit spatial finite-difference operators require solving systems of linear equations. We show that it is possible to merge these two sets of linear systems, one from implicit temporal discretizations and the other from implicit spatial discretizations, to reduce the amount of computations to develop a highly efficient and accurate seismic modeling algorithm. We give the complete derivations of the implicit splitting time integration method and the implicit spatial finite-difference operators, and present the resulting discretized formulas for the scalar wave equation. We conduct a thorough numerical analysis on grid dispersions of this new implicit modeling method. We show that implicit spatial finite-difference operators greatly improve the accuracy of the implicit splitting time integration simulation results with only a slight increase in computational time, compared with explicit spatial finite-difference operators. We further verify this conclusion by both 2D and 3D numerical examples. © 2012 Society of Exploration Geophysicists.

  18. Implicit finite-difference simulations of seismic wave propagation

    KAUST Repository

    Chu, Chunlei

    2012-03-01

    We propose a new finite-difference modeling method, implicit both in space and in time, for the scalar wave equation. We use a three-level implicit splitting time integration method for the temporal derivative and implicit finite-difference operators of arbitrary order for the spatial derivatives. Both the implicit splitting time integration method and the implicit spatial finite-difference operators require solving systems of linear equations. We show that it is possible to merge these two sets of linear systems, one from implicit temporal discretizations and the other from implicit spatial discretizations, to reduce the amount of computations to develop a highly efficient and accurate seismic modeling algorithm. We give the complete derivations of the implicit splitting time integration method and the implicit spatial finite-difference operators, and present the resulting discretized formulas for the scalar wave equation. We conduct a thorough numerical analysis on grid dispersions of this new implicit modeling method. We show that implicit spatial finite-difference operators greatly improve the accuracy of the implicit splitting time integration simulation results with only a slight increase in computational time, compared with explicit spatial finite-difference operators. We further verify this conclusion by both 2D and 3D numerical examples. © 2012 Society of Exploration Geophysicists.

  19. Implicit memory. Retention without remembering.

    Science.gov (United States)

    Roediger, H L

    1990-09-01

    Explicit measures of human memory, such as recall or recognition, reflect conscious recollection of the past. Implicit tests of retention measure transfer (or priming) from past experience on tasks that do not require conscious recollection of recent experiences for their performance. The article reviews research on the relation between explicit and implicit memory. The evidence points to substantial differences between standard explicit and implicit tests, because many variables create dissociations between these tests. For example, although pictures are remembered better than words on explicit tests, words produce more priming than do pictures on several implicit tests. These dissociations may implicate different memory systems that subserve distinct memorial functions, but the present argument is that many dissociations can be understood by appealing to general principles that apply to both explicit and implicit tests. Phenomena studied under the rubric of implicit memory may have important implications in many other fields, including social cognition, problem solving, and cognitive development.

  20. Semantically Enhanced Recommender Systems

    Science.gov (United States)

    Ruiz-Montiel, Manuela; Aldana-Montes, José F.

    Recommender Systems have become a significant area in the context of web personalization, given the large amount of available data. Ontologies can be widely taken advantage of in recommender systems, since they provide a means of classifying and discovering of new information about the items to recommend, about user profiles and even about their context. We have developed a semantically enhanced recommender system based on this kind of ontologies. In this paper we present a description of the proposed system.

  1. Intelligent Knowledge Recommendation Methods for R&D Knowledge Portals

    Institute of Scientific and Technical Information of China (English)

    KIM Jongwoo; LEE Hongjoo; PARK Sungjoo

    2004-01-01

    The personalization in knowledge portals and knowledge management systems is mainly performed based on users' explicitly specified categories and keywords. The explicit specification approach requires users' participation to start personalization services, and has limitation to adapt changes of users' preference. This paper suggests two implicit personalization approaches: automatic user category assignment method and automatic keyword profile generation method. The performances of the implicit personalization approaches are compared with traditional personalization approach using an Internet news site experiment. The result of the experiment shows that the suggested personalization approaches provide sufficient recommendation effectiveness with lessening users'unwanted involvement in personalization process.

  2. An implicit iterative scheme for solving large systems of linear equations

    International Nuclear Information System (INIS)

    Barry, J.M.; Pollard, J.P.

    1986-12-01

    An implicit iterative scheme for the solution of large systems of linear equations arising from neutron diffusion studies is presented. The method is applied to three-dimensional reactor studies and its performance is compared with alternative iterative approaches

  3. Recommender systems and the social web leveraging tagging data for recommender systems

    CERN Document Server

    Gedikli, Fatih

    2013-01-01

    There is an increasing demand for recommender systems due to the information overload users are facing on the Web. The goal of a recommender system is to provide personalized recommendations of products or services to users. With the advent of the Social Web, user-generated content has enriched the social dimension of the Web. As user-provided content data also tells us something about the user, one can learn the user's individual preferences from the Social Web. This opens up completely new opportunities and challenges for recommender systems research. Fatih Gedikli deals with the question of

  4. Recommender systems in knowledge-mining

    Science.gov (United States)

    Volna, Eva

    2017-07-01

    The subject of the paper is to analyse the possibilities of application of recommender systems in the field of data mining. The work focuses on three basic types of recommender systems (collaborative, content-based and hybrid). The goal of the article is to evaluate which of these three concepts of recommender systems provides forecast with the lowest error rate in the domain of recommending movies. This target is fulfilled by the practical part of the work - at first, the own recommender system was designed and created, capable of obtaining movies recommendation from the database based on the user's preferences. Next, we verified experimentally which recommender system produces more accurate results.

  5. Information transfer via implicit encoding with delay time modulation in a time-delay system

    Energy Technology Data Exchange (ETDEWEB)

    Kye, Won-Ho, E-mail: whkye@kipo.go.kr [Korean Intellectual Property Office, Government Complex Daejeon Building 4, 189, Cheongsa-ro, Seo-gu, Daejeon 302-701 (Korea, Republic of)

    2012-08-20

    A new encoding scheme for information transfer with modulated delay time in a time-delay system is proposed. In the scheme, the message is implicitly encoded into the modulated delay time. The information transfer rate as a function of encoding redundancy in various noise scales is presented and it is analyzed that the implicit encoding scheme (IES) has stronger resistance against channel noise than the explicit encoding scheme (EES). In addition, its advantages in terms of secure communication and feasible applications are discussed. -- Highlights: ► We propose new encoding scheme with delay time modulation. ► The message is implicitly encoded with modulated delay time. ► The proposed scheme shows stronger resistance against channel noise.

  6. The time course of explicit and implicit categorization.

    Science.gov (United States)

    Smith, J David; Zakrzewski, Alexandria C; Herberger, Eric R; Boomer, Joseph; Roeder, Jessica L; Ashby, F Gregory; Church, Barbara A

    2015-10-01

    Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization.

  7. Mining and representing recommendations in actively evolving recommender systems

    DEFF Research Database (Denmark)

    Assent, Ira

    2010-01-01

    Recommender systems provide an automatic means of filtering out interesting items, usually based on past similarity of user ratings. In previous work, we have suggested a model that allows users to actively build a recommender network. Users express trust, obtain transparency, and grow (anonymous......) recommender connections. In this work, we propose mining such active systems to generate easily understandable representations of the recommender network. Users may review these representations to provide active feedback. This approach further enhances the quality of recommendations, especially as topics...... of interest change over time. Most notably, it extends the amount of control users have over the model that the recommender network builds of their interests....

  8. Age effects on explicit and implicit memory

    Directory of Open Access Journals (Sweden)

    Emma eWard

    2013-09-01

    Full Text Available It is well documented that explicit memory (e.g., recognition declines with age. In contrast, many argue that implicit memory (e.g., priming is preserved in healthy aging. For example, priming on tasks such as perceptual identification is often not statistically different in groups of young and older adults. Such observations are commonly taken as evidence for distinct explicit and implicit learning/memory systems. In this article we discuss several lines of evidence that challenge this view. We describe how patterns of differential age-related decline may arise from differences in the ways in which the two forms of memory are commonly measured, and review recent research suggesting that under improved measurement methods, implicit memory is not age-invariant. Formal computational models are of considerable utility in revealing the nature of underlying systems. We report the results of applying single and multiple-systems models to data on age effects in implicit and explicit memory. Model comparison clearly favours the single-system view. Implications for the memory systems debate are discussed.

  9. Age effects on explicit and implicit memory.

    Science.gov (United States)

    Ward, Emma V; Berry, Christopher J; Shanks, David R

    2013-01-01

    It is well-documented that explicit memory (e.g., recognition) declines with age. In contrast, many argue that implicit memory (e.g., priming) is preserved in healthy aging. For example, priming on tasks such as perceptual identification is often not statistically different in groups of young and older adults. Such observations are commonly taken as evidence for distinct explicit and implicit learning/memory systems. In this article we discuss several lines of evidence that challenge this view. We describe how patterns of differential age-related decline may arise from differences in the ways in which the two forms of memory are commonly measured, and review recent research suggesting that under improved measurement methods, implicit memory is not age-invariant. Formal computational models are of considerable utility in revealing the nature of underlying systems. We report the results of applying single and multiple-systems models to data on age effects in implicit and explicit memory. Model comparison clearly favors the single-system view. Implications for the memory systems debate are discussed.

  10. Low-storage implicit/explicit Runge-Kutta schemes for the simulation of stiff high-dimensional ODE systems

    Science.gov (United States)

    Cavaglieri, Daniele; Bewley, Thomas

    2015-04-01

    Implicit/explicit (IMEX) Runge-Kutta (RK) schemes are effective for time-marching ODE systems with both stiff and nonstiff terms on the RHS; such schemes implement an (often A-stable or better) implicit RK scheme for the stiff part of the ODE, which is often linear, and, simultaneously, a (more convenient) explicit RK scheme for the nonstiff part of the ODE, which is often nonlinear. Low-storage RK schemes are especially effective for time-marching high-dimensional ODE discretizations of PDE systems on modern (cache-based) computational hardware, in which memory management is often the most significant computational bottleneck. In this paper, we develop and characterize eight new low-storage implicit/explicit RK schemes which have higher accuracy and better stability properties than the only low-storage implicit/explicit RK scheme available previously, the venerable second-order Crank-Nicolson/Runge-Kutta-Wray (CN/RKW3) algorithm that has dominated the DNS/LES literature for the last 25 years, while requiring similar storage (two, three, or four registers of length N) and comparable floating-point operations per timestep.

  11. Cognitive load disrupts implicit theory-of-mind processing.

    Science.gov (United States)

    Schneider, Dana; Lam, Rebecca; Bayliss, Andrew P; Dux, Paul E

    2012-08-01

    Eye movements in Sally-Anne false-belief tasks appear to reflect the ability to implicitly monitor the mental states of other individuals (theory of mind, or ToM). It has recently been proposed that an early-developing, efficient, and automatically operating ToM system subserves this ability. Surprisingly absent from the literature, however, is an empirical test of the influence of domain-general executive processing resources on this implicit ToM system. In the study reported here, a dual-task method was employed to investigate the impact of executive load on eye movements in an implicit Sally-Anne false-belief task. Under no-load conditions, adult participants displayed eye movement behavior consistent with implicit belief processing, whereas evidence for belief processing was absent for participants under cognitive load. These findings indicate that the cognitive system responsible for implicitly tracking beliefs draws at least minimally on executive processing resources. Thus, even the most low-level processing of beliefs appears to reflect a capacity-limited operation.

  12. Classification of Recommender Expertise in the Wikipedia Recommender System

    DEFF Research Database (Denmark)

    Jensen, Christian D.; Pilkauskas, Povilas; Lefévre, Thomas

    2011-01-01

    to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles which emphasizes...... an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System....... feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article...

  13. Classification of Recommender Expertise in the Wikipedia Recommender System

    DEFF Research Database (Denmark)

    Jensen, Christian D.; Pilkauskas, Povilas; Lefevre, Thomas

    2011-01-01

    to the quality of articles. The Wikipedia Recommender System (WRS) was developed to help users determine the credibility of articles based on feedback from other Wikipedia users. The WRS implements a collaborative filtering system with trust metrics, i.e., it provides a rating of articles "which emphasizes...... an evaluation of four existing knowledge classification schemes with respect to these requirements. This evaluation helped us identify a classification scheme, which we have implemented in the current version of the Wikipedia Recommender System....... feedback from recommenders that the user has agreed with in the past. This exposes the problem that most recommenders are not equally competent in all subject areas. The first WRS prototype did not include an evaluation of the areas of expertise of recommenders, so the trust metric used in the article...

  14. A Flexible Electronic Commerce Recommendation System

    Science.gov (United States)

    Gong, Songjie

    Recommendation systems have become very popular in E-commerce websites. Many of the largest commerce websites are already using recommender technologies to help their customers find products to purchase. An electronic commerce recommendation system learns from a customer and recommends products that the customer will find most valuable from among the available products. But most recommendation methods are hard-wired into the system and they support only fixed recommendations. This paper presented a framework of flexible electronic commerce recommendation system. The framework is composed by user model interface, recommendation engine, recommendation strategy model, recommendation technology group, user interest model and database interface. In the recommender strategy model, the method can be collaborative filtering, content-based filtering, mining associate rules method, knowledge-based filtering method or the mixed method. The system mapped the implementation and demand through strategy model, and the whole system would be design as standard parts to adapt to the change of the recommendation strategy.

  15. Towards a Formal Treatment of Implicit Invocation

    National Research Council Canada - National Science Library

    Dingel, J

    1997-01-01

    .... A formal computational model for implicit invocation is presented. We develop a verification framework for implicit invocation that is based on Jones' rely/guarantee reasoning for concurrent systems Jon83,St(phi)91...

  16. Understanding and Overcoming Implicit Gender Bias in Plastic Surgery.

    Science.gov (United States)

    Phillips, Nicole A; Tannan, Shruti C; Kalliainen, Loree K

    2016-11-01

    Although explicit sex-based discrimination has largely been deemed unacceptable in professional settings, implicit gender bias persists and results in a significant lack of parity in plastic surgery and beyond. Implicit gender bias is the result of a complex interplay of cultural and societal expectations, learned behaviors, and standardized associations. As such, both male and female surgeons are subject to its influence. A review of the literature was conducted, examining theories of gender bias, current manifestations of gender bias in plastic surgery and other fields, and interventions designed to address gender bias. Multiple studies demonstrate persistent gender bias that impacts female physicians at all levels of training. Several institutions have enacted successful interventions to identify and address gender bias. Explicit gender bias has largely disappeared, yet unconscious or implicit gender bias persists. A wide-scale commitment to addressing implicit gender bias in plastic surgery is necessary and overdue. Recommendations include immediate actions that can be undertaken on an individual basis, and changes that should be implemented at a national and international level by leaders in the field.

  17. How "implicit" are implicit color effects in memory?

    Science.gov (United States)

    Zimmer, Hubert D; Steiner, Astrid; Ecker, Ullrich K H

    2002-01-01

    Processing colored pictures of objects results in a preference to choose the former color for a specific object in a subsequent color choice test (Wippich & Mecklenbräuker, 1998). We tested whether this implicit memory effect is independent of performances in episodic color recollection (recognition). In the study phase of Experiment 1, the color of line drawings was either named or its appropriateness was judged. We found only weak implicit memory effects for categorical color information. In Experiment 2, silhouettes were colored by subjects during the study phase. Performances in both the implicit and the explicit test were good. Selections of "old" colors in the implicit test, though, were almost completely confined to items for which the color was also remembered explicitly. In Experiment 3, we applied the opposition technique in order to check whether we could find any implicit effects regarding items for which no explicit color recollection was possible. This was not the case. We therefore draw the conclusion that implicit color preference effects are not independent of explicit recollection, and that they are probably based on the same episodic memory traces that are used in explicit tests.

  18. Reducing Implicit Prejudice

    OpenAIRE

    Lai, Calvin; Nosek, Brian; Hoffman, Kelly

    2017-01-01

    Implicit prejudice are social preferences that exist outside of conscious awareness or conscious control. We summarize evidence for three mechanisms that influence the expression of implicit prejudice: associative change, contextual change, and change in control over implicit prejudice. We then review the evidence (or lack thereof) for five open issues in implicit prejudice reduction research: 1) what shows effectiveness in real-world application; 2) what doesn’t work for implicit prejudice r...

  19. Recommendation based on trust diffusion model.

    Science.gov (United States)

    Yuan, Jinfeng; Li, Li

    2014-01-01

    Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure.

  20. An implicit adaptation algorithm for a linear model reference control system

    Science.gov (United States)

    Mabius, L.; Kaufman, H.

    1975-01-01

    This paper presents a stable implicit adaptation algorithm for model reference control. The constraints for stability are found using Lyapunov's second method and do not depend on perfect model following between the system and the reference model. Methods are proposed for satisfying these constraints without estimating the parameters on which the constraints depend.

  1. Recommender Systems in Commercial Use

    OpenAIRE

    Aldrich, Susan E.

    2011-01-01

    Commercial recommender systems are deployed by marketing teams to increase revenue and/or personalize user experience. Marketers evaluate recommender systems not on its algorithms but on how well the vendor‘s expertise and interfaces will support achieving business goals. Driven by a business model that pays based on recommendation success, vendors guide clients through continuous optimization of recommendations. While recommender technology is mature, the solutions and market are still young...

  2. Recommendation systems in software engineering

    CERN Document Server

    Robillard, Martin P; Walker, Robert J; Zimmermann, Thomas

    2014-01-01

    With the growth of public and private data stores and the emergence of off-the-shelf data-mining technology, recommendation systems have emerged that specifically address the unique challenges of navigating and interpreting software engineering data.This book collects, structures and formalizes knowledge on recommendation systems in software engineering. It adopts a pragmatic approach with an explicit focus on system design, implementation, and evaluation. The book is divided into three parts: "Part I - Techniques" introduces basics for building recommenders in software engineering, including techniques for collecting and processing software engineering data, but also for presenting recommendations to users as part of their workflow.?"Part II - Evaluation" summarizes methods and experimental designs for evaluating recommendations in software engineering.?"Part III - Applications" describes needs, issues and solution concepts involved in entire recommendation systems for specific software engineering tasks, fo...

  3. Diffusion-based recommendation with trust relations on tripartite graphs

    Science.gov (United States)

    Wang, Ximeng; Liu, Yun; Zhang, Guangquan; Xiong, Fei; Lu, Jie

    2017-08-01

    The diffusion-based recommendation approach is a vital branch in recommender systems, which successfully applies physical dynamics to make recommendations for users on bipartite or tripartite graphs. Trust links indicate users’ social relations and can provide the benefit of reducing data sparsity. However, traditional diffusion-based algorithms only consider rating links when making recommendations. In this paper, the complementarity of users’ implicit and explicit trust is exploited, and a novel resource-allocation strategy is proposed, which integrates these two kinds of trust relations on tripartite graphs. Through empirical studies on three benchmark datasets, our proposed method obtains better performance than most of the benchmark algorithms in terms of accuracy, diversity and novelty. According to the experimental results, our method is an effective and reasonable way to integrate additional features into the diffusion-based recommendation approach.

  4. Recommender Systems for Learning

    CERN Document Server

    Manouselis, Nikos; Verbert, Katrien; Duval, Erik

    2013-01-01

    Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

  5. An implicit Smooth Particle Hydrodynamic code

    Energy Technology Data Exchange (ETDEWEB)

    Knapp, Charles E. [Univ. of New Mexico, Albuquerque, NM (United States)

    2000-05-01

    An implicit version of the Smooth Particle Hydrodynamic (SPH) code SPHINX has been written and is working. In conjunction with the SPHINX code the new implicit code models fluids and solids under a wide range of conditions. SPH codes are Lagrangian, meshless and use particles to model the fluids and solids. The implicit code makes use of the Krylov iterative techniques for solving large linear-systems and a Newton-Raphson method for non-linear corrections. It uses numerical derivatives to construct the Jacobian matrix. It uses sparse techniques to save on memory storage and to reduce the amount of computation. It is believed that this is the first implicit SPH code to use Newton-Krylov techniques, and is also the first implicit SPH code to model solids. A description of SPH and the techniques used in the implicit code are presented. Then, the results of a number of tests cases are discussed, which include a shock tube problem, a Rayleigh-Taylor problem, a breaking dam problem, and a single jet of gas problem. The results are shown to be in very good agreement with analytic solutions, experimental results, and the explicit SPHINX code. In the case of the single jet of gas case it has been demonstrated that the implicit code can do a problem in much shorter time than the explicit code. The problem was, however, very unphysical, but it does demonstrate the potential of the implicit code. It is a first step toward a useful implicit SPH code.

  6. Approximate Implicitization Using Linear Algebra

    Directory of Open Access Journals (Sweden)

    Oliver J. D. Barrowclough

    2012-01-01

    Full Text Available We consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore well suited to floating-point implementation in computer-aided geometric design (CAGD systems. We unify the approaches under the names of commonly known polynomial basis functions and consider various theoretical and practical aspects of the algorithms. We offer new methods for a least squares approach to approximate implicitization using orthogonal polynomials, which tend to be faster and more numerically stable than some existing algorithms. We propose several simple propositions relating the properties of the polynomial bases to their implicit approximation properties.

  7. Introduction on health recommender systems.

    Science.gov (United States)

    Sanchez-Bocanegra, C L; Sanchez-Laguna, F; Sevillano, J L

    2015-01-01

    People are looking for appropriate health information which they are concerned about. The Internet is a great resource of this kind of information, but we have to be careful if we don't want to get harmful info. Health recommender systems are becoming a new wave for apt health information as systems suggest the best data according to the patients' needs.The main goals of health recommender systems are to retrieve trusted health information from the Internet, to analyse which is suitable for the user profile and select the best that can be recommended, to adapt their selection methods according to the knowledge domain and to learn from the best recommendations.A brief definition of recommender systems will be given and an explanation of how are they incorporated in the health sector. A description of the main elementary recommender methods as well as their most important problems will also be made. And, to finish, the state of the art will be described.

  8. The explicit and implicit dance in psychoanalytic change.

    Science.gov (United States)

    Fosshage, James L

    2004-02-01

    How the implicit/non-declarative and explicit/declarative cognitive domains interact is centrally important in the consideration of effecting change within the psychoanalytic arena. Stern et al. (1998) declare that long-lasting change occurs in the domain of implicit relational knowledge. In the view of this author, the implicit and explicit domains are intricately intertwined in an interactive dance within a psychoanalytic process. The author views that a spirit of inquiry (Lichtenberg, Lachmann & Fosshage 2002) serves as the foundation of the psychoanalytic process. Analyst and patient strive to explore, understand and communicate and, thereby, create a 'spirit' of interaction that contributes, through gradual incremental learning, to new implicit relational knowledge. This spirit, as part of the implicit relational interaction, is a cornerstone of the analytic relationship. The 'inquiry' more directly brings explicit/declarative processing to the foreground in the joint attempt to explore and understand. The spirit of inquiry in the psychoanalytic arena highlights both the autobiographical scenarios of the explicit memory system and the mental models of the implicit memory system as each contributes to a sense of self, other, and self with other. This process facilitates the extrication and suspension of the old models, so that new models based on current relational experience can be gradually integrated into both memory systems for lasting change.

  9. Cryptographically-Enhanced Privacy for Recommender Systems

    NARCIS (Netherlands)

    Jeckmans, Arjan

    2014-01-01

    Automated recommender systems are used to help people find interesting content or persons in the vast amount of information available via the internet. There are different types of recommender systems, for example collaborative filtering systems and content-based recommender systems. However, all

  10. EPS Mid-Career Award 2011. Are there multiple memory systems? Tests of models of implicit and explicit memory.

    Science.gov (United States)

    Shanks, David R; Berry, Christopher J

    2012-01-01

    This article reviews recent work aimed at developing a new framework, based on signal detection theory, for understanding the relationship between explicit (e.g., recognition) and implicit (e.g., priming) memory. Within this framework, different assumptions about sources of memorial evidence can be framed. Application to experimental results provides robust evidence for a single-system model in preference to multiple-systems models. This evidence comes from several sources including studies of the effects of amnesia and ageing on explicit and implicit memory. The framework allows a range of concepts in current memory research, such as familiarity, recollection, fluency, and source memory, to be linked to implicit memory. More generally, this work emphasizes the value of modern computational modelling techniques in the study of learning and memory.

  11. Implicit-explicit (IMEX) Runge-Kutta methods for non-hydrostatic atmospheric models

    Science.gov (United States)

    Gardner, David J.; Guerra, Jorge E.; Hamon, François P.; Reynolds, Daniel R.; Ullrich, Paul A.; Woodward, Carol S.

    2018-04-01

    The efficient simulation of non-hydrostatic atmospheric dynamics requires time integration methods capable of overcoming the explicit stability constraints on time step size arising from acoustic waves. In this work, we investigate various implicit-explicit (IMEX) additive Runge-Kutta (ARK) methods for evolving acoustic waves implicitly to enable larger time step sizes in a global non-hydrostatic atmospheric model. The IMEX formulations considered include horizontally explicit - vertically implicit (HEVI) approaches as well as splittings that treat some horizontal dynamics implicitly. In each case, the impact of solving nonlinear systems in each implicit ARK stage in a linearly implicit fashion is also explored. The accuracy and efficiency of the IMEX splittings, ARK methods, and solver options are evaluated on a gravity wave and baroclinic wave test case. HEVI splittings that treat some vertical dynamics explicitly do not show a benefit in solution quality or run time over the most implicit HEVI formulation. While splittings that implicitly evolve some horizontal dynamics increase the maximum stable step size of a method, the gains are insufficient to overcome the additional cost of solving a globally coupled system. Solving implicit stage systems in a linearly implicit manner limits the solver cost but this is offset by a reduction in step size to achieve the desired accuracy for some methods. Overall, the third-order ARS343 and ARK324 methods performed the best, followed by the second-order ARS232 and ARK232 methods.

  12. Recommendation System for Adaptive Learning.

    Science.gov (United States)

    Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

    2018-01-01

    An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

  13. Framing (implicitly) matters

    DEFF Research Database (Denmark)

    Anderson, Joel; Antalikova, Radka

    2014-01-01

    Denmark is currently experiencing the highest immigration rate in its modern history. Population surveys indicate that negative public attitudes toward immigrants actually stem from attitudes toward their (perceived) Islamic affiliation. We used a framing paradigm to investigate the explicit...... and implicit attitudes of Christian and Atheist Danes toward targets framed as Muslims or as immigrants. The results showed that explicit and implicit attitudes were more negative when the target was framed as a Muslim, rather than as an immigrant. Interestingly, implicit attitudes were qualified...... by the participants’ religion. Specifically, analyses revealed that Christians demonstrated more negative implicit attitudes toward immigrants than Muslims. Conversely, Atheists demonstrated more negative implicit attitudes toward Muslims than Atheists. These results suggest a complex relationship between religion...

  14. Modelling Implicit Communication in Multi-Agent Systems with Hybrid Input/Output Automata

    Directory of Open Access Journals (Sweden)

    Marta Capiluppi

    2012-10-01

    Full Text Available We propose an extension of Hybrid I/O Automata (HIOAs to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. To this end we decided to specialize some variables of the HIOAs whose values are functions both of time and space. We call them world variables. Basically they are treated similarly to the other variables of HIOAs, but they have the function of representing the interaction of each automaton with the surrounding environment, hence they can be output, input or internal variables. Since these special variables have the role of simulating implicit communication, their dynamics are specified both in time and space, because they model the perturbations induced by the agent to the environment, and the perturbations of the environment as perceived by the agent. Parallel composition of world variables is slightly different from parallel composition of the other variables, since their signals are summed. The theory is illustrated through a simple example of agents systems.

  15. RECOMMENDER SYSTEMS IN E-COMMERCE APPLICATIONS

    Directory of Open Access Journals (Sweden)

    Gyöngyvér KOVÁCS

    2016-12-01

    Full Text Available One of the major problem with online shopping is finingd the right product, because finding the right product presumes that we know its name, but in most cases it is not so. For this reason the users need help in the process of online searching/shopping. Recommender systems have became a popular technique and strategy for helping users to select desirable products or services. In the past few years the recommender systems have changed from novelties used by a few big e-commerce sites, to serious business tools that are re-shaping the world of e-commerce. In this paper, we provide a brief overview of the classification of recommendation systems based on technology used to create recommendations, and inputs they need from the customers. Furthermore we analyze a few algorithms used by recommender systems and we will also present some marketing recommender systems and their comparative analysis.

  16. Implicit and explicit ethnocentrism: revisiting the ideologies of prejudice.

    Science.gov (United States)

    Cunningham, William A; Nezlek, John B; Banaji, Mahzarin R

    2004-10-01

    Two studies investigated relationships among individual differences in implicit and explicit prejudice, right-wing ideology, and rigidity in thinking. The first study examined these relationships focusing on White Americans' prejudice toward Black Americans. The second study provided the first test of implicit ethnocentrism and its relationship to explicit ethnocentrism by studying the relationship between attitudes toward five social groups. Factor analyses found support for both implicit and explicit ethnocentrism. In both studies, mean explicit attitudes toward out groups were positive, whereas implicit attitudes were negative, suggesting that implicit and explicit prejudices are distinct; however, in both studies, implicit and explicit attitudes were related (r = .37, .47). Latent variable modeling indicates a simple structure within this ethnocentric system, with variables organized in order of specificity. These results lead to the conclusion that (a) implicit ethnocentrism exists and (b) it is related to and distinct from explicit ethnocentrism.

  17. Recommended system of application and development

    Science.gov (United States)

    Wang, Wei

    2018-04-01

    A recommender system is a project that helps users identify their wishes and needs. The recommender system has been successfully applied to many e-commerce environments, such as news, film, music, books and other areas of recommendation. This paper mainly discusses the application of recommendation technology in software engineering, data and knowledge engineering, configurable projects and persuasion technology, and summarizes the development trend of recommendation technology in the future.

  18. Implicit measure for yoga research: Yoga implicit association test

    Directory of Open Access Journals (Sweden)

    Judu V Ilavarasu

    2014-01-01

    Conclusions: Implicit measures may be used in the yoga field to assess constructs, which are difficult to self-report or may have social desirability threat. Y-IAT may be used to evaluate implicit preference toward yoga.

  19. Hybrid context aware recommender systems

    Science.gov (United States)

    Jain, Rajshree; Tyagi, Jaya; Singh, Sandeep Kumar; Alam, Taj

    2017-10-01

    Recommender systems and context awareness is currently a vital field of research. Most hybrid recommendation systems implement content based and collaborative filtering techniques whereas this work combines context and collaborative filtering. The paper presents a hybrid context aware recommender system for books and movies that gives recommendations based on the user context as well as user or item similarity. It also addresses the issue of dimensionality reduction using weighted pre filtering based on dynamically entered user context and preference of context. This unique step helps to reduce the size of dataset for collaborative filtering. Bias subtracted collaborative filtering is used so as to consider the relative rating of a particular user and not the absolute values. Cosine similarity is used as a metric to determine the similarity between users or items. The unknown ratings are calculated and evaluated using MSE (Mean Squared Error) in test and train datasets. The overall process of recommendation has helped to personalize recommendations and give more accurate results with reduced complexity in collaborative filtering.

  20. Implicit memory in music and language.

    Science.gov (United States)

    Ettlinger, Marc; Margulis, Elizabeth H; Wong, Patrick C M

    2011-01-01

    Research on music and language in recent decades has focused on their overlapping neurophysiological, perceptual, and cognitive underpinnings, ranging from the mechanism for encoding basic auditory cues to the mechanism for detecting violations in phrase structure. These overlaps have most often been identified in musicians with musical knowledge that was acquired explicitly, through formal training. In this paper, we review independent bodies of work in music and language that suggest an important role for implicitly acquired knowledge, implicit memory, and their associated neural structures in the acquisition of linguistic or musical grammar. These findings motivate potential new work that examines music and language comparatively in the context of the implicit memory system.

  1. Implicit Memory in Music and Language

    Directory of Open Access Journals (Sweden)

    Marc eEttlinger

    2011-09-01

    Full Text Available Research on music and language in recent decades has focused on their overlapping neurophysiological, perceptual, and cognitive underpinnings, ranging from the mechanism for encoding basic auditory cues to the mechanism for detecting violations in phrase structure. These overlaps have most often been identified in musicians with musical knowledge that was acquired explicitly, through formal training. In this paper, we review independent bodies of work in music and language that suggest an important role for implicitly acquired knowledge, implicit memory, and their associated neural structures in the acquisition of linguistic or musical grammar. These findings motivate potential new work that examines music and language comparatively in the context of the implicit memory system.

  2. Ubiquitous Multicriteria Clinic Recommendation System.

    Science.gov (United States)

    Chen, Toly

    2016-05-01

    Advancements in information, communication, and sensor technologies have led to new opportunities in medical care and education. Patients in general prefer visiting the nearest clinic, attempt to avoid waiting for treatment, and have unequal preferences for different clinics and doctors. Therefore, to enable patients to compare multiple clinics, this study proposes a ubiquitous multicriteria clinic recommendation system. In this system, patients can send requests through their cell phones to the system server to obtain a clinic recommendation. Once the patient sends this information to the system, the system server first estimates the patient's speed according to the detection results of a global positioning system. It then applies a fuzzy integer nonlinear programming-ordered weighted average approach to assess four criteria and finally recommends a clinic with maximal utility to the patient. The proposed methodology was tested in a field experiment, and the experimental results showed that it is advantageous over two existing methods in elevating the utilities of recommendations. In addition, such an advantage was shown to be statistically significant.

  3. Severity of explicit memory impairment due to Alzheimer's disease improves effectiveness of implicit learning.

    Science.gov (United States)

    Klimkowicz-Mrowiec, Aleksandra; Slowik, Agnieszka; Krzywoszanski, Lukasz; Herzog-Krzywoszanska, Radosława; Szczudlik, Andrzej

    2008-04-01

    Consistent evidence from human and experimental animals studies indicates that memory is organized into two relatively independent systems with different functions and brain mechanisms. The explicit memory system, dependent on the hippocampus and adjacent medial temporal lobe structures, refers to conscious knowledge acquisition and intentional recollection of previous experiences. The implicit memory system, dependent on the striatum, refers to learning of complex information without awareness or intention. The functioning of implicit memory can be observed in progressive, gradual improvement across many trials in performance on implicit learning tasks. The influence of explicit memory on implicit memory has not been precisely identified yet. According to data from some studies, explicit memory seems to exhibit no influence on implicit memory,whereas the other studies indicate that explicit memory may inhibit or facilitate implicit memory. The analysis of performance on implicit learning tasks in patients with different severity of explicit memory impairment due to Alzheimer's disease allows one to identify the potential influence of the explicit memory system on the implicit memory system. 51 patients with explicit memory impairment due to Alzheimer's disease (AD) and 36 healthy controls were tested. Explicit memory was examined by means of a battery of neuropsychological tests. Implicit habit learning was examined on probabilistic classification task (weather prediction task). Patients with moderate explicit memory impairment performed the implicit task significantly better than those with mild AD and controls. Results of our study support the hypothesis of competition between the implicit and explicit memory systems in humans.

  4. I trust it, but I don't know why: effects of implicit attitudes toward automation on trust in an automated system.

    Science.gov (United States)

    Merritt, Stephanie M; Heimbaugh, Heather; LaChapell, Jennifer; Lee, Deborah

    2013-06-01

    This study is the first to examine the influence of implicit attitudes toward automation on users' trust in automation. Past empirical work has examined explicit (conscious) influences on user level of trust in automation but has not yet measured implicit influences. We examine concurrent effects of explicit propensity to trust machines and implicit attitudes toward automation on trust in an automated system. We examine differential impacts of each under varying automation performance conditions (clearly good, ambiguous, clearly poor). Participants completed both a self-report measure of propensity to trust and an Implicit Association Test measuring implicit attitude toward automation, then performed an X-ray screening task. Automation performance was manipulated within-subjects by varying the number and obviousness of errors. Explicit propensity to trust and implicit attitude toward automation did not significantly correlate. When the automation's performance was ambiguous, implicit attitude significantly affected automation trust, and its relationship with propensity to trust was additive: Increments in either were related to increases in trust. When errors were obvious, a significant interaction between the implicit and explicit measures was found, with those high in both having higher trust. Implicit attitudes have important implications for automation trust. Users may not be able to accurately report why they experience a given level of trust. To understand why users trust or fail to trust automation, measurements of implicit and explicit predictors may be necessary. Furthermore, implicit attitude toward automation might be used as a lever to effectively calibrate trust.

  5. Implicit and Explicit Associations with Erotic Stimuli in Sexually Functional and Dysfunctional Men.

    Science.gov (United States)

    van Lankveld, Jacques; Odekerken, Ingrid; Kok-Verhoeven, Lydia; van Hooren, Susan; de Vries, Peter; van den Hout, Anja; Verboon, Peter

    2015-08-01

    Although conceptual models of sexual functioning have suggested a major role for implicit cognitive processing in sexual functioning, this has thus far, only been investigated in women. The aim of this study was to investigate the role of implicit cognition in sexual functioning in men. Men with (N = 29) and without sexual dysfunction (N = 31) were compared. Participants performed two single-target implicit association tests (ST-IAT), measuring the implicit association of visual erotic stimuli with attributes representing, respectively, valence ('liking') and motivation ('wanting'). Participants also rated the erotic pictures that were shown in the ST-IAT on the dimensions of valence, attractiveness, and sexual excitement to assess their explicit associations with these erotic stimuli. Participants completed the International Index of Erectile Functioning for a continuous measure of sexual functioning. Unexpectedly, compared with sexually functional men, sexually dysfunctional men were found to show stronger implicit associations of erotic stimuli with positive valence than with negative valence. Level of sexual functioning, however, was not predicted by explicit nor implicit associations. Level of sexual distress was predicted by explicit valence ratings, with positive ratings predicting higher levels of sexual distress. Men with and without sexual dysfunction differed significantly with regard to implicit liking. Research recommendations and implications are discussed. © 2015 International Society for Sexual Medicine.

  6. Uncovering the information core in recommender systems

    Science.gov (United States)

    Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhou, Tao

    2014-08-01

    With the rapid growth of the Internet and overwhelming amount of information that people are confronted with, recommender systems have been developed to effectively support users' decision-making process in online systems. So far, much attention has been paid to designing new recommendation algorithms and improving existent ones. However, few works considered the different contributions from different users to the performance of a recommender system. Such studies can help us improve the recommendation efficiency by excluding irrelevant users. In this paper, we argue that in each online system there exists a group of core users who carry most of the information for recommendation. With them, the recommender systems can already generate satisfactory recommendation. Our core user extraction method enables the recommender systems to achieve 90% of the accuracy of the top-L recommendation by taking only 20% of the users into account. A detailed investigation reveals that these core users are not necessarily the large-degree users. Moreover, they tend to select high quality objects and their selections are well diversified.

  7. Using the Implicit Association Test to Assess Children's Implicit Attitudes toward Smoking.

    Science.gov (United States)

    Andrews, Judy A; Hampson, Sarah E; Greenwald, Anthony G; Gordon, Judith; Widdop, Chris

    2010-09-01

    The development and psychometric properties of an Implicit Association Test (IAT) measuring implicit attitude toward smoking among fifth grade children were described. The IAT with "sweets" as the contrast category resulted in higher correlations with explicit attitudes than did the IAT with "healthy foods" as the contrast category. Children with family members who smoked (versus non-smoking) and children who were high in sensation seeking (versus low) had a significantly more favorable implicit attitude toward smoking. Further, implicit attitudes became less favorable after engaging in tobacco prevention activities targeting risk perceptions of addiction. Results support the reliability and validity of this version of the IAT and illustrate its usefulness in assessing young children's implicit attitude toward smoking.

  8. RECOMMENDER SYSTEMS IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Cleomar Valois Batista Jr

    2011-12-01

    Full Text Available The continued and diversified growth of social networks has changed the way in which users interact with them. With these changes, what once was limited to social contact is now used for exchanging ideas and opinions, creating the need for new features. Users have so much information at their fingertips that they are unable to process it by themselves; hence, the need to develop new tools. Recommender systems were developed to address this need and many techniques were used for different approaches to the problem. To make relevant recommendations, these systems use large sets of data, not taking the social network of the user into consideration. Developing a recommender system that takes into account the social network of the user is another way of tackling the problem. The purpose of this project is to use the theory of six degrees of separation (Watts 2003 amongst users of a social network to enhance existing recommender systems.

  9. A unitary signal-detection model of implicit and explicit memory.

    Science.gov (United States)

    Berry, Christopher J; Shanks, David R; Henson, Richard N A

    2008-10-01

    Do dissociations imply independent systems? In the memory field, the view that there are independent implicit and explicit memory systems has been predominantly supported by dissociation evidence. Here, we argue that many of these dissociations do not necessarily imply distinct memory systems. We review recent work with a single-system computational model that extends signal-detection theory (SDT) to implicit memory. SDT has had a major influence on research in a variety of domains. The current work shows that it can be broadened even further in its range of application. Indeed, the single-system model that we present does surprisingly well in accounting for some key dissociations that have been taken as evidence for independent implicit and explicit memory systems.

  10. An implicit finite-difference operator for the Helmholtz equation

    KAUST Repository

    Chu, Chunlei; Stoffa, Paul L.

    2012-01-01

    We have developed an implicit finite-difference operator for the Laplacian and applied it to solving the Helmholtz equation for computing the seismic responses in the frequency domain. This implicit operator can greatly improve the accuracy of the simulation results without adding significant extra computational cost, compared with the corresponding conventional explicit finite-difference scheme. We achieved this by taking advantage of the inherently implicit nature of the Helmholtz equation and merging together the two linear systems: one from the implicit finite-difference discretization of the Laplacian and the other from the discretization of the Helmholtz equation itself. The end result of this simple yet important merging manipulation is a single linear system, similar to the one resulting from the conventional explicit finite-difference discretizations, without involving any differentiation matrix inversions. We analyzed grid dispersions of the discrete Helmholtz equation to show the accuracy of this implicit finite-difference operator and used two numerical examples to demonstrate its efficiency. Our method can be extended to solve other frequency domain wave simulation problems straightforwardly. © 2012 Society of Exploration Geophysicists.

  11. An implicit finite-difference operator for the Helmholtz equation

    KAUST Repository

    Chu, Chunlei

    2012-07-01

    We have developed an implicit finite-difference operator for the Laplacian and applied it to solving the Helmholtz equation for computing the seismic responses in the frequency domain. This implicit operator can greatly improve the accuracy of the simulation results without adding significant extra computational cost, compared with the corresponding conventional explicit finite-difference scheme. We achieved this by taking advantage of the inherently implicit nature of the Helmholtz equation and merging together the two linear systems: one from the implicit finite-difference discretization of the Laplacian and the other from the discretization of the Helmholtz equation itself. The end result of this simple yet important merging manipulation is a single linear system, similar to the one resulting from the conventional explicit finite-difference discretizations, without involving any differentiation matrix inversions. We analyzed grid dispersions of the discrete Helmholtz equation to show the accuracy of this implicit finite-difference operator and used two numerical examples to demonstrate its efficiency. Our method can be extended to solve other frequency domain wave simulation problems straightforwardly. © 2012 Society of Exploration Geophysicists.

  12. A general framework for intelligent recommender systems

    Directory of Open Access Journals (Sweden)

    Jose Aguilar

    2017-07-01

    Full Text Available In this paper, we propose a general framework for an intelligent recommender system that extends the concept of a knowledge-based recommender system. The intelligent recommender system exploits knowledge, learns, discovers new information, infers preferences and criticisms, among other things. For that, the framework of an intelligent recommender system is defined by the following components: knowledge representation paradigm, learning methods, and reasoning mechanisms. Additionally, it has five knowledge models about the different aspects that we can consider during a recommendation: users, items, domain, context and criticisms. The mix of the components exploits the knowledge, updates it and infers, among other things. In this work, we implement one intelligent recommender system based on this framework, using Fuzzy Cognitive Maps (FCMs. Next, we test the performance of the intelligent recommender system with specialized criteria linked to the utilization of the knowledge in order to test the versatility and performance of the framework.

  13. Effects of pretesting implicit self-determined motivation on behavioral engagement: evidence for the mere measurement effect at the implicit level.

    Science.gov (United States)

    Keatley, David A; Clarke, David D; Ferguson, Eamonn; Hagger, Martin S

    2014-01-01

    Research into individuals' intended behavior and performance has traditionally adopted explicitly measured, self-report constructs, and outcomes. More recently, research has shown that completing explicit self-report measures of constructs may effect subsequent behavior, termed the "mere measurement" effect. The aim of the present experiment was to investigate whether implicit measures of motivation showed a similar mere measurement effect on subsequent behavior. It may be the case that measuring the implicit systems affects subsequent implicit interventions (e.g., priming), observable on subsequent behavior. Priming manipulations were also given to participants in order to investigate the interaction between measurement and priming of motivation. Initially, a 2 [implicit association test (IAT: present vs. absent) ×2 (Prime: autonomous vs. absent) and a 2 (IAT: present vs. absent) × 2 (Prime: controlled vs. absent)] between participants designs were conducted, these were them combined into a 2 (IAT: present vs. absent) ×3 (Prime: autonomous vs. controlled vs. absent) between participants design, with attempts at a novel task taken as the outcome measure. Implicit measure completion significantly decreased behavioral engagement. Priming autonomous motivation significantly facilitated, and controlled motivation significantly inhibited performance. Finally, there was a significant implicit measurement × priming interaction, such that priming autonomous motivation only improved performance in the absence of the implicit measure. Overall, this research provides an insight into the effects of implicit measurement and priming of motivation and the combined effect of completing both tasks on behavior.

  14. Sexy but often unreliable: the impact of unreliability on the replicability of experimental findings with implicit measures.

    Science.gov (United States)

    Lebel, Etienne P; Paunonen, Sampo V

    2011-04-01

    Implicit measures have contributed to important insights in almost every area of psychology. However, various issues and challenges remain concerning their use, one of which is their considerable variation in reliability, with many implicit measures having questionable reliability. The goal of the present investigation was to examine an overlooked consequence of this liability with respect to replication, when such implicit measures are used as dependent variables in experimental studies. Using a Monte Carlo simulation, the authors demonstrate that a higher level of unreliability in such dependent variables is associated with substantially lower levels of replicability. The results imply that this overlooked consequence can have far-reaching repercussions for the development of a cumulative science. The authors recommend the routine assessment and reporting of the reliability of implicit measures and also urge the improvement of implicit measures with low reliability.

  15. Receiving recommendations and providing feedback : the user-experience of a recommender system

    NARCIS (Netherlands)

    Knijnenburg, B.P.; Willemsen, M.C.; Hirtbach, S.; Buccafurri, F.; Semeraro, G.

    2010-01-01

    This paper systematically evaluates the user experience of a recommender system. Using both behavioral data and subjective measures of user experience, we demonstrate that choice satisfaction and system effectiveness increase when a system provides personalized recommendations (compared to the same

  16. The Definition of Novelty in Recommendation System

    Directory of Open Access Journals (Sweden)

    Liang Zhang

    2013-01-01

    Full Text Available With the development of information technology and application of the Internet, People gradually entered the time of information overload from information scarcity. User satisfaction with recommender systems is related not only to how accurately the system recommends but also to how much it supports the user’s decision making. Novelty is one of the important metrics of customer satisfaction. There is an increasing realization in the Recommender Systems (RS field that novelty is fundamental qualities of recommendation effectiveness and added-value. This paper combed research results about definition and algorithm of novel recommendation, and starting from the meaning of "novel", defined novelty of item in recommendation system. Experiment proved using the definition of novelty to recommend can effectively recognize the item that the user is familiar with and ensure certain accuracy.

  17. Explaining the user experience of recommender systems

    NARCIS (Netherlands)

    Knijnenburg, B.P.; Willemsen, M.C.; Gantner, Z.; Soncu, H.; Newell, C.

    2012-01-01

    Research on recommender systems typically focuses on the accuracy of prediction algorithms. Because accuracy only partially constitutes the user experience of a recommender system, this paper proposes a framework that takes a user-centric approach to recommender system evaluation. The framework

  18. Advanced Semi-Implicit Method (ASIM) for hyperbolic two-fluid model

    International Nuclear Information System (INIS)

    Lee, Sung Jae; Chung, Moon Sun

    2003-01-01

    Introducing the interfacial pressure jump terms based on the surface tension into the momentum equations of two-phase two-fluid model, the system of governing equations is turned mathematically into the hyperbolic system. The eigenvalues of the equation system become always real representing the void wave and the pressure wave propagation speeds as shown in the previous manuscript. To solve the interfacial pressure jump terms with void fraction gradients implicitly, the conventional semi-implicit method should be modified as an intermediate iteration method for void fraction at fractional time step. This Advanced Semi-Implicit Method (ASIM) then becomes stable without conventional additive terms. As a consequence, including the interfacial pressure jump terms with the advanced semi-implicit method, the numerical solutions of typical two-phase problems can be more stable and sound than those calculated exclusively by using any other terms like virtual mass, or artificial viscosity

  19. Avoiding congestion in recommender systems

    International Nuclear Information System (INIS)

    Ren, Xiaolong; Lü, Linyuan; Liu, Runran; Zhang, Jianlin

    2014-01-01

    Recommender systems use the historical activities and personal profiles of users to uncover their preferences and recommend objects. Most of the previous methods are based on objects’ (and/or users’) similarity rather than on their difference. Such approaches are subject to a high risk of increasingly exposing users to a narrowing band of popular objects. As a result, a few objects may be recommended to an enormous number of users, resulting in the problem of recommendation congestion, which is to be avoided, especially when the recommended objects are limited resources. In order to quantitatively measure a recommendation algorithm's ability to avoid congestion, we proposed a new metric inspired by the Gini index, which is used to measure the inequality of the individual wealth distribution in an economy. Besides this, a new recommendation method called directed weighted conduction (DWC) was developed by considering the heat conduction process on a user–object bipartite network with different thermal conductivities. Experimental results obtained for three benchmark data sets showed that the DWC algorithm can effectively avoid system congestion, and greatly improve the novelty and diversity, while retaining relatively high accuracy, in comparison with the state-of-the-art methods. (paper)

  20. Multilevel Drift-Implicit Tau-Leap

    KAUST Repository

    Ben Hammouda, Chiheb

    2016-01-06

    The dynamics of biochemical reactive systems with small copy numbers of one or more reactant molecules is dominated by stochastic effects. For those systems, discrete state-space and stochastic simulation approaches were proved to be more relevant than continuous state-space and deterministic ones. In systems characterized by having simultaneously fast and slowtimescales, the existing discrete space-state stochastic path simulation methods such as the stochastic simulation algorithm (SSA) and the explicit tauleap method can be very slow. Implicit approximations were developed in the literature to improve numerical stability and provide efficient simulation algorithms for those systems. In this work, we propose an efficient Multilevel Monte Carlo method in the spirit of the work by Anderson and Higham (2012) that uses drift-implicit tau-leap approximations at levels where the explicit tauleap method is not applicable due to numerical stability issues. We present numerical examples that illustrate the performance of the proposed method.

  1. Making sense in asset markets: Strategies for Implicit Organizations

    Directory of Open Access Journals (Sweden)

    Johannes M. Lehner

    2015-12-01

    Full Text Available While asset markets are traditionally left to economic inquiry, the paper shows that there is both a legal possibility and an incentive for organizing within such markets and for exercising market share-based strategic maneuvering. It proposes, based on sensemaking theory, Implicit Organizations in asset markets to exploit equivocality for momentum trading strategies. An Implicit Organization fulfills the criteria of an organization, while maintaining the image of a perfect market. Its members coordinate via market signals and fixed investment time windows to ensure positive returns to strategic maneuvering in asset markets. In support of hypotheses derived from sensemaking theory, results of empirical studies from two different investment contexts (Xetra and NYSE provide evidence that equivocal analysts’ recommendations predict investment returns after a fixed time period.

  2. Promoting cold-start items in recommender systems.

    Science.gov (United States)

    Liu, Jin-Hu; Zhou, Tao; Zhang, Zi-Ke; Yang, Zimo; Liu, Chuang; Li, Wei-Min

    2014-01-01

    As one of the major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, the so-called item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. Interestingly, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely, these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs.

  3. Promoting Cold-Start Items in Recommender Systems

    Science.gov (United States)

    Liu, Jin-Hu; Zhou, Tao; Zhang, Zi-Ke; Yang, Zimo; Liu, Chuang; Li, Wei-Min

    2014-01-01

    As one of the major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, the so-called item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. Interestingly, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely, these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs. PMID:25479013

  4. Recommendation-Aware Smartphone Sensing System

    OpenAIRE

    Chen, Mu-Yen; Wu, Ming-Ni; Chen, Chia-Chen; Chen, Young-Long; Lin, Hsien-En

    2014-01-01

    The context-aware concept is to reduce the gap between users and information systems so that the information systems actively get to understand users’ context and demand and in return provide users with better experience. This study integrates the concept of context-aware with association algorithms to establish the context-aware recommendation systems (CARS). The CARS contains three modules and provides the product recommendations for users with their smartphone. First, the simple RSSI Indoo...

  5. Recent developments in affective recommender systems

    Science.gov (United States)

    Katarya, Rahul; Verma, Om Prakash

    2016-11-01

    Recommender systems (RSs) are playing a significant role since 1990s as they provide relevant, personalized information to the users over the internet. Lots of work have been done in information filtering, utilization, and application related to RS. However, an important area recently draws our attention which is affective recommender system. Affective recommender system (ARS) is latest trending area of research, as publication in this domain are few and recently published. ARS is associated with human behaviour, human factors, mood, senses, emotions, facial expressions, body gesture and physiological with human-computer interaction (HCI). Due to this assortment and various interests, more explanation is required, as it is in premature phase and growing as compared to other fields. So we have done literature review (LR) in the affective recommender systems by doing classification, incorporate reputed articles published from the year 2003 to February 2016. We include articles which highlight, analyse, and perform a study on affective recommender systems. This article categorizes, synthesizes, and discusses the research and development in ARS. We have classified and managed ARS papers according to different perspectives: research gaps, nature, algorithm or method adopted, datasets, the platform on executed, types of information and evaluation techniques applied. The researchers and professionals will positively support this survey article for understanding the current position, research in affective recommender systems and will guide future trends, opportunity and research focus in ARS.

  6. Implicit learning as an ability.

    Science.gov (United States)

    Kaufman, Scott Barry; Deyoung, Colin G; Gray, Jeremy R; Jiménez, Luis; Brown, Jamie; Mackintosh, Nicholas

    2010-09-01

    The ability to automatically and implicitly detect complex and noisy regularities in the environment is a fundamental aspect of human cognition. Despite considerable interest in implicit processes, few researchers have conceptualized implicit learning as an ability with meaningful individual differences. Instead, various researchers (e.g., Reber, 1993; Stanovich, 2009) have suggested that individual differences in implicit learning are minimal relative to individual differences in explicit learning. In the current study of English 16-17year old students, we investigated the association of individual differences in implicit learning with a variety of cognitive and personality variables. Consistent with prior research and theorizing, implicit learning, as measured by a probabilistic sequence learning task, was more weakly related to psychometric intelligence than was explicit associative learning, and was unrelated to working memory. Structural equation modeling revealed that implicit learning was independently related to two components of psychometric intelligence: verbal analogical reasoning and processing speed. Implicit learning was also independently related to academic performance on two foreign language exams (French, German). Further, implicit learning was significantly associated with aspects of self-reported personality, including intuition, Openness to Experience, and impulsivity. We discuss the implications of implicit learning as an ability for dual-process theories of cognition, intelligence, personality, skill learning, complex cognition, and language acquisition. 2010 Elsevier B.V. All rights reserved.

  7. How do incentives lead to deception in advisor-client interactions? Explicit and implicit strategies of self-interested deception.

    Science.gov (United States)

    Mackinger, Barbara; Jonas, Eva

    2012-01-01

    When confronted with important questions we like to rely on the advice of experts. However, uncertainty can occur regarding advisors' motivation to pursue self-interest and deceive the client. This can especially occur when the advisor has the possibility to receive an incentive by recommending a certain alternative. We investigated how the possibility to pursue self-interest led to explicit strategic behavior (bias in recommendation and transfer of information) and to implicit strategic behavior (bias in information processing: evaluation and memory). In Study 1 explicit strategic behavior could be identified: self-interested advisors recommended more often the self-serving alternative and transferred more self-interested biased information to their client compared to the advisor without specific interest. Also deception through implicit strategic behavior was identified: self-interested advisors biased the evaluation of information less in favor of the client compared to the control group. Self-interested advisors also remembered conflicting information regarding their self-interest worse compared to advisors without self-interest. In Study 2 beside self-interest we assessed accountability which interacted with self-interest and increased the bias: when accountability was high advisor's self-interest led to higher explicit strategic behavior (less transfer of conflicting information), and to higher implicit strategic behavior (devaluated and remembered less conflicting information). Both studies identified implicit strategic behavior as mediator which can explain the relation between self-interest and explicit strategic behavior. Results of both studies suggest that self-interested advisors use explicit and implicit strategic behavior to receive an incentive. Thus, advisors do not only consciously inform their clients "self-interested," but they are influenced unconsciously by biased information processing - a tendency which even increased with high

  8. Can implicit motivation be measured?

    DEFF Research Database (Denmark)

    Kraus, Alexandra; Scholderer, Joachim

    According to recent neurobiological models, food choices are influenced by two separate reward systems: motivational wanting (incentive salience of the reward) and affective liking (hedonic pleasure associated with the reward). Both are assumed to have conscious and unconscious components. Applying...... such promising conceptual frameworks within consumer research would not only be helpful for understanding human appetite but also has implications for predicting consumer behaviour. Since the affective liking system has strong similarities to contemporary attitude theories, implicit and explicit measures...... of evaluation could be applied. However, no comparable procedures have been developed for the motivational wanting component; generally accepted “low-tech” measures are therefore still lacking! Thus, the aim of this study was to develop and test implicit measures of wanting that can be used as dependent...

  9. Awareness of Implicit Attitudes

    Science.gov (United States)

    Hahn, Adam; Judd, Charles M.; Hirsh, Holen K.; Blair, Irene V.

    2013-01-01

    Research on implicit attitudes has raised questions about how well people know their own attitudes. Most research on this question has focused on the correspondence between measures of implicit attitudes and measures of explicit attitudes, with low correspondence interpreted as showing that people have little awareness of their implicit attitudes. We took a different approach and directly asked participants to predict their results on upcoming IAT measures of implicit attitudes toward five different social groups. We found that participants were surprisingly accurate in their predictions. Across four studies, predictions were accurate regardless of whether implicit attitudes were described as true attitudes or culturally learned associations (Studies 1 and 2), regardless of whether predictions were made as specific response patterns (Study 1) or as conceptual responses (Studies 2–4), and regardless of how much experience or explanation participants received before making their predictions (Study 4). Study 3 further suggested that participants’ predictions reflected unique insight into their own implicit responses, beyond intuitions about how people in general might respond. Prediction accuracy occurred despite generally low correspondence between implicit and explicit measures of attitudes, as found in prior research. All together, the research findings cast doubt on the belief that attitudes or evaluations measured by the IAT necessarily reflect unconscious attitudes. PMID:24294868

  10. Personalized Recommender System for Digital Libraries

    Science.gov (United States)

    Omisore, M. O.; Samuel, O. W.

    2014-01-01

    The huge amount of information available online has given rise to personalization and filtering systems. Recommender systems (RS) constitute a specific type of information filtering technique that present items according to user's interests. In this research, a web-based personalized recommender system capable of providing learners with books that…

  11. Electromagnetic direct implicit PIC simulation

    International Nuclear Information System (INIS)

    Langdon, A.B.

    1983-01-01

    Interesting modelling of intense electron flow has been done with implicit particle-in-cell simulation codes. In this report, the direct implicit PIC simulation approach is applied to simulations that include full electromagnetic fields. The resulting algorithm offers advantages relative to moment implicit electromagnetic algorithms and may help in our quest for robust and simpler implicit codes

  12. Reducing Prejudice With Labels: Shared Group Memberships Attenuate Implicit Bias and Expand Implicit Group Boundaries.

    Science.gov (United States)

    Scroggins, W Anthony; Mackie, Diane M; Allen, Thomas J; Sherman, Jeffrey W

    2016-02-01

    In three experiments, we used a novel Implicit Association Test procedure to investigate the impact of group memberships on implicit bias and implicit group boundaries. Results from Experiment 1 indicated that categorizing targets using a shared category reduced implicit bias by increasing the extent to which positivity was associated with Blacks. Results from Experiment 2 revealed that shared group membership, but not mere positivity of a group membership, was necessary to reduce implicit bias. Quadruple process model analyses indicated that changes in implicit bias caused by shared group membership are due to changes in the way that targets are evaluated, not to changes in the regulation of evaluative bias. Results from Experiment 3 showed that categorizing Black targets into shared group memberships expanded implicit group boundaries. © 2015 by the Society for Personality and Social Psychology, Inc.

  13. An Agent Framework of Tourism Recommender System

    Directory of Open Access Journals (Sweden)

    Jia Zhi Yang

    2016-01-01

    Full Text Available This paper proposes the development of an Agent framework for tourism recommender system. The recommender system can be featured as an online web application which is capable of generating a personalized list of preference attractions for tourists. Traditional technologies of classical recommender system application domains, such as collaborative filtering, content-based filtering and content-based filtering are effectively adopted in the framework. In the framework they are constructed as Agents that can generate recommendations respectively. Recommender Agent can generate recommender information by integrating the recommendations of Content-based Agent, collaborative filtering-based Agent and constraint-based Agent. In order to make the performance more effective, linear combination method of data fusion is applied. User interface is provided by the tourist Agent in form of webpages and mobile app.

  14. Effects of pretesting implicit self-determined motivation on behavioural engagement: Evidence for the mere measurement effect at the implicit level

    Directory of Open Access Journals (Sweden)

    David A Keatley

    2014-02-01

    Full Text Available Research into individuals’ intended behavior and performance has traditionally adopted explicitly-measured, self-report constructs and outcomes. More recently, research has shown that completing explicit self-report measures of constructs may effect subsequent behavior, termed the ‘mere measurement’ effect. The aim of the present experiment was to investigate whether implicit measures of motivation showed a similar mere measurement effect on subsequent behavior. It may be the case that measuring the implicit systems affects subsequent implicit interventions (e.g., priming, observable on subsequent behaviour. Priming manipulations were also given to participants in order to investigate the interaction between measurement and priming of motivation. Initially, a 2 (IAT: present vs absent x2 (Prime: autonomous vs absent and a 2 (IAT: present vs absent x 2 (Prime: controlled vs. absent between participants designs were conducted, these were them combined into a 2 (IAT: present vs absent x3 (Prime: autonomous vs controlled vs absent between participants design, with attempts at a novel task taken as the outcome measure. Implicit measure completion significantly decreased behavioral engagement. Priming autonomous motivation significantly facilitated, and controlled motivation significantly inhibited performance. Finally, there was a significant implicit measurement x priming interaction, such that priming autonomous motivation only improved performance in the absence of the implicit measure. Overall, this research provides an insight into the effects of implicit measurement and priming of motivation and the combined effect of completing both tasks on behavior.

  15. Recommender Systems in Technology Enhanced Learning

    NARCIS (Netherlands)

    Manouselis, Nikos; Drachsler, Hendrik; Vuorikari, Riina; Hummel, Hans; Koper, Rob

    2010-01-01

    Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H. G. K., & Koper, R. (2011). Recommender Systems in Technology Enhanced Learning. In P. B. Kantor, F. Ricci, L. Rokach, & B. Shapira (Eds.), Recommender Systems Handbook (pp. 387-415). Berlin: Springer.

  16. Semi-implicit magnetohydrodynamic calculations

    International Nuclear Information System (INIS)

    Schnack, D.D.; Barnes, D.C.; Mikic, Z.; Harned, D.S.; Caramana, E.J.

    1987-01-01

    A semi-implicit algorithm for the solution of the nonlinear, three-dimensional, resistive MHD equations in cylindrical geometry is presented. The specific model assumes uniform density and pressure, although this is not a restriction of the method. The spatial approximation employs finite differences in the radial coordinate, and the pseudo-spectral algorithm in the periodic poloidal and axial coordinates. A leapfrog algorithm is used to advance wave-like terms; advective terms are treated with a simple predictor--corrector method. The semi-implicit term is introduced as a simple modification to the momentum equation. Dissipation is treated implicitly. The resulting algorithm is unconditionally stable with respect to normal modes. A general discussion of the semi-implicit method is given, and specific forms of the semi-implicit operator are compared in physically relevant test cases. Long-time simulations are presented. copyright 1987 Academic Press, Inc

  17. Panorama of recommender systems to support learning

    OpenAIRE

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in Technology-Enhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from 35 different countries have been investigated and categorised according to a given classification framework. The reviewed systems have been classified into 7 clusters according to their c...

  18. Panorama of Recommender Systems to Support Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga C.; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender

  19. weHelp: A Reference Architecture for Social Recommender Systems.

    Science.gov (United States)

    Sheth, Swapneel; Arora, Nipun; Murphy, Christian; Kaiser, Gail

    2010-01-01

    Recommender systems have become increasingly popular. Most of the research on recommender systems has focused on recommendation algorithms. There has been relatively little research, however, in the area of generalized system architectures for recommendation systems. In this paper, we introduce weHelp : a reference architecture for social recommender systems - systems where recommendations are derived automatically from the aggregate of logged activities conducted by the system's users. Our architecture is designed to be application and domain agnostic. We feel that a good reference architecture will make designing a recommendation system easier; in particular, weHelp aims to provide a practical design template to help developers design their own well-modularized systems.

  20. Implicit Bias and Mental Health Professionals: Priorities and Directions for Research.

    Science.gov (United States)

    Merino, Yesenia; Adams, Leslie; Hall, William J

    2018-06-01

    This Open Forum explores the role of implicit bias along the mental health care continuum, which may contribute to mental health disparities among vulnerable populations. Emerging research shows that implicit bias is prevalent among service providers. These negative or stigmatizing attitudes toward population groups are held at a subconscious level and are automatically activated during practitioner-client encounters. The authors provide examples of how implicit bias may impede access to care, clinical screening and diagnosis, treatment processes, and crisis response. They also discuss how implicit attitudes may manifest at the intersection between mental health and criminal justice institutions. Finally, they discuss the need for more research on the impact of implicit bias on health practices throughout the mental health system, including the development of interventions to address implicit bias among mental health professionals.

  1. How do incentives lead to deception in advisors-client interactions? Explicit and implicit strategies of self-interested deception.

    Directory of Open Access Journals (Sweden)

    Barbara eMackinger

    2012-12-01

    Full Text Available When confronted with important questions we like to rely on the advice of experts. However, uncertainty can occur regarding advisors’ motivation to pursue self-interest and deceive the client. This can especially occur when the advisor has the possibility to receive an incentive by recommending a certain alternative. We investigated how the possibility to pursue self-interest led to explicit strategic behavior (bias in recommendation and transfer of information and to implicit strategic behavior (bias in information processing: evaluation and memory. In Study 1 explicit strategic behavior could be identified: Self-interested advisors recommended more often the self-serving alternative and transferred more self-interested biased information to their client compared to the advisor without specific interest. Also deception through implicit strategic behavior was identified: Self-interested advisors biased the evaluation of information less in favor of the client compared to the control group. Self-interested advisors also remembered conflicting information regarding their self-interest worse compared to advisors without self-interest. In Study 2 beside self-interest we assessed accountability which interacted with self-interest and increased the bias: When accountability was high advisor’s self-interest led to higher explicit strategic behavior (less transfer of conflicting information, and to higher implicit strategic behavior (devaluated and remembered less conflicting information. Both studies identified implicit strategic behavior as mediator which can explain the relation between self-interest and explicit strategic behavior. Results of both studies suggest that self-interested advisors use explicit and implicit strategic behavior to receive an incentive. Thus, advisors do not only consciously inform their clients self-interested, but they are influenced unconsciously by biased information processing—a tendency which even increased with

  2. How Do Incentives Lead to Deception in Advisor–Client Interactions? Explicit and Implicit Strategies of Self-Interested Deception

    Science.gov (United States)

    Mackinger, Barbara; Jonas, Eva

    2012-01-01

    When confronted with important questions we like to rely on the advice of experts. However, uncertainty can occur regarding advisors’ motivation to pursue self-interest and deceive the client. This can especially occur when the advisor has the possibility to receive an incentive by recommending a certain alternative. We investigated how the possibility to pursue self-interest led to explicit strategic behavior (bias in recommendation and transfer of information) and to implicit strategic behavior (bias in information processing: evaluation and memory). In Study 1 explicit strategic behavior could be identified: self-interested advisors recommended more often the self-serving alternative and transferred more self-interested biased information to their client compared to the advisor without specific interest. Also deception through implicit strategic behavior was identified: self-interested advisors biased the evaluation of information less in favor of the client compared to the control group. Self-interested advisors also remembered conflicting information regarding their self-interest worse compared to advisors without self-interest. In Study 2 beside self-interest we assessed accountability which interacted with self-interest and increased the bias: when accountability was high advisor’s self-interest led to higher explicit strategic behavior (less transfer of conflicting information), and to higher implicit strategic behavior (devaluated and remembered less conflicting information). Both studies identified implicit strategic behavior as mediator which can explain the relation between self-interest and explicit strategic behavior. Results of both studies suggest that self-interested advisors use explicit and implicit strategic behavior to receive an incentive. Thus, advisors do not only consciously inform their clients “self-interested,” but they are influenced unconsciously by biased information processing – a tendency which even increased with high

  3. Recommender Systems in Technology Enhanced Learning

    NARCIS (Netherlands)

    Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Santos, Olga

    2010-01-01

    Manouselis, N., Drachsler, H., Verbert, K., & Santos, C. S. (Eds.) (2010). Recommender System in Technology Enhanced Learning. Elsevier Procedia Computer Science: Volume 1, Issue 2. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL). September, 29-30,

  4. A parallel nearly implicit time-stepping scheme

    OpenAIRE

    Botchev, Mike A.; van der Vorst, Henk A.

    2001-01-01

    Across-the-space parallelism still remains the most mature, convenient and natural way to parallelize large scale problems. One of the major problems here is that implicit time stepping is often difficult to parallelize due to the structure of the system. Approximate implicit schemes have been suggested to circumvent the problem. These schemes have attractive stability properties and they are also very well parallelizable. The purpose of this article is to give an overall assessment of the pa...

  5. TOURISM RECOMMENDATION SYSTEM: EMPIRICAL INVESTIGATION

    OpenAIRE

    Biljana PETREVSKA; Saso KOCESKI

    2012-01-01

    The paper makes an attempt to justify the necessity of implementing recommendation system which will assist tourists in identification of their ideal holiday. The proposed recommendation system based on collaborative filtering notes positive impulses in the case of Macedonia. A software module is developed being capable to generate a personalized list of favorable and tailor-made items. The research outcomes indicate that the designed national tourism web portal can provide satisfactory perfo...

  6. Calculations of the electromechanical transfer processes using implicit methods of numerical integration

    Energy Technology Data Exchange (ETDEWEB)

    Pogosyan, T A

    1983-01-01

    The article is dedicated to the solution of systems of differential equations which describe the transfer processes in an electric power system (EES) by implicit methods of numerical integration. The distinguishing feature of the implicit methods (Euler's reverse method and the trapeze method) is their absolute stability and, consequently, the relatively small accumulation of errors in each step of integration. Therefore, they are found to be very convenient for solving problems of electric power engineering, when the transfer processes are described by a rigid system of differential equations. The rigidity is associated with the range of values of the time constants considered. The advantage of the implicit methods over explicit are shown in a specific example (calculation of the dynamic stability of the simplest electric power system), along with the field of use of the implicit methods and the expedience of their use in power engineering problems.

  7. How explicit and implicit test instructions in an implicit learning task affect performance.

    Directory of Open Access Journals (Sweden)

    Arnaud Witt

    Full Text Available Typically developing children aged 5 to 8 years were exposed to artificial grammar learning. Following an implicit exposure phase, half of the participants received neutral instructions at test while the other half received instructions making a direct, explicit reference to the training phase. We first aimed to assess whether implicit learning operated in the two test conditions. We then evaluated the differential impact of age on learning performances as a function of test instructions. The results showed that performance did not vary as a function of age in the implicit instructions condition, while age effects emerged when explicit instructions were employed at test. However, performance was affected differently by age and the instructions given at test, depending on whether the implicit learning of short or long units was assessed. These results suggest that the claim that the implicit learning process is independent of age needs to be revised.

  8. Do recommender systems benefit users? a modeling approach

    Science.gov (United States)

    Yeung, Chi Ho

    2016-04-01

    Recommender systems are present in many web applications to guide purchase choices. They increase sales and benefit sellers, but whether they benefit customers by providing relevant products remains less explored. While in many cases the recommended products are relevant to users, in other cases customers may be tempted to purchase the products only because they are recommended. Here we introduce a model to examine the benefit of recommender systems for users, and find that recommendations from the system can be equivalent to random draws if one always follows the recommendations and seldom purchases according to his or her own preference. Nevertheless, with sufficient information about user preferences, recommendations become accurate and an abrupt transition to this accurate regime is observed for some of the studied algorithms. On the other hand, we find that high estimated accuracy indicated by common accuracy metrics is not necessarily equivalent to high real accuracy in matching users with products. This disagreement between estimated and real accuracy serves as an alarm for operators and researchers who evaluate recommender systems merely with accuracy metrics. We tested our model with a real dataset and observed similar behaviors. Finally, a recommendation approach with improved accuracy is suggested. These results imply that recommender systems can benefit users, but the more frequently a user purchases the recommended products, the less relevant the recommended products are in matching user taste.

  9. A trajectory-based recommender system for tourism

    OpenAIRE

    Baraglia, Ranieri; Frattari, Claudio; Muntean, Cristina Ioana; Nardini, Franco Maria; Silvestri, Fabrizio

    2012-01-01

    Recommendation systems provide focused information to users on a set of objects belonging to a specific domain. The proposed recommender system provides personalized suggestions about touristic points of interest. The system generates recommendations, consisting of touristic places, according to the current position of a tourist and previously collected data describing tourist movements in a touristic location/city. The touristic sites correspond to a set of points of interest identified a pr...

  10. Therapy Decision Support Based on Recommender System Methods.

    Science.gov (United States)

    Gräßer, Felix; Beckert, Stefanie; Küster, Denise; Schmitt, Jochen; Abraham, Susanne; Malberg, Hagen; Zaunseder, Sebastian

    2017-01-01

    We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender , are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.

  11. Seeing the forest through the trees: a comparison of different IAT variants measuring implicit alcohol associations

    NARCIS (Netherlands)

    Houben, K.; Nosek, B.; Wiers, R.W.

    2010-01-01

    Dual-process models propose that addictive behaviors are determined by an implicit, impulsive system and an explicit, reflective system. Consistent with these models, research has demonstrated implicit affective associations with alcohol, using the Implicit Association Test (IAT), that predict

  12. Therapy Decision Support Based on Recommender System Methods

    Directory of Open Access Journals (Sweden)

    Felix Gräßer

    2017-01-01

    Full Text Available We present a system for data-driven therapy decision support based on techniques from the field of recommender systems. Two methods for therapy recommendation, namely, Collaborative Recommender and Demographic-based Recommender, are proposed. Both algorithms aim to predict the individual response to different therapy options using diverse patient data and recommend the therapy which is assumed to provide the best outcome for a specific patient and time, that is, consultation. The proposed methods are evaluated using a clinical database incorporating patients suffering from the autoimmune skin disease psoriasis. The Collaborative Recommender proves to generate both better outcome predictions and recommendation quality. However, due to sparsity in the data, this approach cannot provide recommendations for the entire database. In contrast, the Demographic-based Recommender performs worse on average but covers more consultations. Consequently, both methods profit from a combination into an overall recommender system.

  13. Recommendation System Based on Fuzzy Cognitive Map

    OpenAIRE

    Wei Liu; Linzhi Gao

    2014-01-01

    With the increase of data volume and visitor volume, the website faces great challenge in the environment of network. How to know the users’ requirements rapidly and effectively and recommend the required information to the user becomes the research direction of all websites. The researchers of recommendation system propose a series of recommendation system models and algorithms for the user. The common challenge faced by these algorithms is how to judge the user intention and recommend...

  14. Privacy in Recommender Systems

    NARCIS (Netherlands)

    Jeckmans, Arjan; Beye, Michael; Erkin, Zekeriya; Erkin, Zekeriya; Hartel, Pieter H.; Lagendijk, Reginald; Tang, Qiang; Ramzan, Naeem; van Zwol, Roelof; Lee, Jong-Seok; Clüver, Kai; Hua, Xian-Sheng

    In many online applications, the range of content that is offered to users is so wide that a need for automated recommender systems arises. Such systems can provide a personalized selection of relevant items to users. In practice, this can help people find entertaining movies, boost sales through

  15. Do Implicit Attitudes Predict Actual Voting Behavior Particularly for Undecided Voters?

    Science.gov (United States)

    Friese, Malte; Smith, Colin Tucker; Plischke, Thomas; Bluemke, Matthias; Nosek, Brian A.

    2012-01-01

    The prediction of voting behavior of undecided voters poses a challenge to psychologists and pollsters. Recently, researchers argued that implicit attitudes would predict voting behavior particularly for undecided voters whereas explicit attitudes would predict voting behavior particularly for decided voters. We tested this assumption in two studies in two countries with distinct political systems in the context of real political elections. Results revealed that (a) explicit attitudes predicted voting behavior better than implicit attitudes for both decided and undecided voters, and (b) implicit attitudes predicted voting behavior better for decided than undecided voters. We propose that greater elaboration of attitudes produces stronger convergence between implicit and explicit attitudes resulting in better predictive validity of both, and less incremental validity of implicit over explicit attitudes for the prediction of voting behavior. However, greater incremental predictive validity of implicit over explicit attitudes may be associated with less elaboration. PMID:22952898

  16. Implicit and semi-implicit schemes in the Versatile Advection Code : numerical tests

    NARCIS (Netherlands)

    Tóth, G.; Keppens, R.; Bochev, Mikhail A.

    1998-01-01

    We describe and evaluate various implicit and semi-implicit time integration schemes applied to the numerical simulation of hydrodynamical and magnetohydrodynamical problems. The schemes were implemented recently in the software package Versatile Advection Code, which uses modern shock capturing

  17. Modeling mutual feedback between users and recommender systems

    Science.gov (United States)

    Zeng, An; Yeung, Chi Ho; Medo, Matúš; Zhang, Yi-Cheng

    2015-07-01

    Recommender systems daily influence our decisions on the Internet. While considerable attention has been given to issues such as recommendation accuracy and user privacy, the long-term mutual feedback between a recommender system and the decisions of its users has been neglected so far. We propose here a model of network evolution which allows us to study the complex dynamics induced by this feedback, including the hysteresis effect which is typical for systems with non-linear dynamics. Despite the popular belief that recommendation helps users to discover new things, we find that the long-term use of recommendation can contribute to the rise of extremely popular items and thus ultimately narrow the user choice. These results are supported by measurements of the time evolution of item popularity inequality in real systems. We show that this adverse effect of recommendation can be tamed by sacrificing part of short-term recommendation accuracy.

  18. A Sentiment-Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework

    Directory of Open Access Journals (Sweden)

    Yibo Wang

    2018-01-01

    Full Text Available Movie recommendation in mobile environment is critically important for mobile users. It carries out comprehensive aggregation of user’s preferences, reviews, and emotions to help them find suitable movies conveniently. However, it requires both accuracy and timeliness. In this paper, a movie recommendation framework based on a hybrid recommendation model and sentiment analysis on Spark platform is proposed to improve the accuracy and timeliness of mobile movie recommender system. In the proposed approach, we first use a hybrid recommendation method to generate a preliminary recommendation list. Then sentiment analysis is employed to optimize the list. Finally, the hybrid recommender system with sentiment analysis is implemented on Spark platform. The hybrid recommendation model with sentiment analysis outperforms the traditional models in terms of various evaluation criteria. Our proposed method makes it convenient and fast for users to obtain useful movie suggestions.

  19. Weighted hybrid technique for recommender system

    Science.gov (United States)

    Suriati, S.; Dwiastuti, Meisyarah; Tulus, T.

    2017-12-01

    Recommender system becomes very popular and has important role in an information system or webpages nowadays. A recommender system tries to make a prediction of which item a user may like based on his activity on the system. There are some familiar techniques to build a recommender system, such as content-based filtering and collaborative filtering. Content-based filtering does not involve opinions from human to make the prediction, while collaborative filtering does, so collaborative filtering can predict more accurately. However, collaborative filtering cannot give prediction to items which have never been rated by any user. In order to cover the drawbacks of each approach with the advantages of other approach, both approaches can be combined with an approach known as hybrid technique. Hybrid technique used in this work is weighted technique in which the prediction score is combination linear of scores gained by techniques that are combined.The purpose of this work is to show how an approach of weighted hybrid technique combining content-based filtering and item-based collaborative filtering can work in a movie recommender system and to show the performance comparison when both approachare combined and when each approach works alone. There are three experiments done in this work, combining both techniques with different parameters. The result shows that the weighted hybrid technique that is done in this work does not really boost the performance up, but it helps to give prediction score for unrated movies that are impossible to be recommended by only using collaborative filtering.

  20. Scientific and educational recommender systems

    Science.gov (United States)

    Guseva, A. I.; Kireev, V. S.; Bochkarev, P. V.; Kuznetsov, I. A.; Philippov, S. A.

    2017-01-01

    This article discusses the questions associated with the use of reference systems in the preparation of graduates in physical function. The objective of this research is creation of model of recommender system user from the sphere of science and education. The detailed review of current scientific and social network for scientists and the problem of constructing recommender systems in this area. The result of this study is to research user information model systems. The model is presented in two versions: the full one - in the form of a semantic network, and short - in a relational form. The relational model is the projection in the form of semantic network, taking into account the restrictions on the amount of bonds that characterize the number of information items (research results), which interact with the system user.

  1. Explicit Pre-Training Instruction Does Not Improve Implicit Perceptual-Motor Sequence Learning

    Science.gov (United States)

    Sanchez, Daniel J.; Reber, Paul J.

    2013-01-01

    Memory systems theory argues for separate neural systems supporting implicit and explicit memory in the human brain. Neuropsychological studies support this dissociation, but empirical studies of cognitively healthy participants generally observe that both kinds of memory are acquired to at least some extent, even in implicit learning tasks. A key…

  2. Private personalized social recommendations in an IPTV system

    Science.gov (United States)

    Elmisery, Ahmed M.

    2014-04-01

    In our connected world, recommender systems have become widely known for their ability to provide expert and personalize referrals to end-users in different domains. The rapid growth of social networks and new kinds of systems so called "social recommender systems" are rising, where recommender systems can be utilized to find a suitable content according to end-users' personal preferences. However, preserving end-users' privacy in social recommender systems is a very challenging problem that might prevent end-users from releasing their own data, which detains the accuracy of extracted referrals. In order to gain accurate referrals, social recommender systems should have the ability to preserve the privacy of end-users registered in this system. In this paper, we present a middleware that runs on end-users' Set-top boxes to conceal their profile data when released for generating referrals, such that computation of recommendation proceeds over the concealed data. The proposed middleware is equipped with two concealment protocols to give users a complete control on the privacy level of their profiles. We present an IPTV network scenario and perform a number of different experiments to test the efficiency and accuracy of our protocols. As supported by the experiments, our protocols maintain the recommendations accuracy with acceptable privacy level.

  3. Inductive reasoning and implicit memory: evidence from intact and impaired memory systems.

    Science.gov (United States)

    Girelli, Luisa; Semenza, Carlo; Delazer, Margarete

    2004-01-01

    In this study, we modified a classic problem solving task, number series completion, in order to explore the contribution of implicit memory to inductive reasoning. Participants were required to complete number series sharing the same underlying algorithm (e.g., +2), differing in both constituent elements (e.g., 2468 versus 57911) and correct answers (e.g., 10 versus 13). In Experiment 1, reliable priming effects emerged, whether primes and targets were separated by four or ten fillers. Experiment 2 provided direct evidence that the observed facilitation arises at central stages of problem solving, namely the identification of the algorithm and its subsequent extrapolation. The observation of analogous priming effects in a severely amnesic patient strongly supports the hypothesis that the facilitation in number series completion was largely determined by implicit memory processes. These findings demonstrate that the influence of implicit processes extends to higher level cognitive domain such as induction reasoning.

  4. Implicit Memory in Multiple Sclerosis

    Directory of Open Access Journals (Sweden)

    G. Latchford

    1993-01-01

    Full Text Available A number of neuropsychological studies have revealed that memory problems are relatively common in patients with multiple sclerosis (MS. It may be useful to compare MS with conditions such as Huntington's disease (HD, which have been referred to as subcortical dementia. A characteristic of these conditions may be an impairment in implicit (unconscious memory, but not in explicit (conscious memory. The present study examined the functioning of explicit and implicit memory in MS. Results showed that implicit memory was not significantly impaired in the MS subjects, and that they were impaired on recall but not recognition. A correlation was found between implicit memory performance and disability status in MS patients. Findings also suggest the possibility of long-term priming of implicit memory in the control subjects. The implications of these results are discussed.

  5. Implicit associations in cybersex addiction: Adaption of an Implicit Association Test with pornographic pictures.

    Science.gov (United States)

    Snagowski, Jan; Wegmann, Elisa; Pekal, Jaro; Laier, Christian; Brand, Matthias

    2015-10-01

    Recent studies show similarities between cybersex addiction and substance dependencies and argue to classify cybersex addiction as a behavioral addiction. In substance dependency, implicit associations are known to play a crucial role, and such implicit associations have not been studied in cybersex addiction, so far. In this experimental study, 128 heterosexual male participants completed an Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) modified with pornographic pictures. Further, problematic sexual behavior, sensitivity towards sexual excitation, tendencies towards cybersex addiction, and subjective craving due to watching pornographic pictures were assessed. Results show positive relationships between implicit associations of pornographic pictures with positive emotions and tendencies towards cybersex addiction, problematic sexual behavior, sensitivity towards sexual excitation as well as subjective craving. Moreover, a moderated regression analysis revealed that individuals who reported high subjective craving and showed positive implicit associations of pornographic pictures with positive emotions, particularly tended towards cybersex addiction. The findings suggest a potential role of positive implicit associations with pornographic pictures in the development and maintenance of cybersex addiction. Moreover, the results of the current study are comparable to findings from substance dependency research and emphasize analogies between cybersex addiction and substance dependencies or other behavioral addictions. Copyright © 2015. Published by Elsevier Ltd.

  6. Assessment of implicit self-esteem in bipolar manic and euthymic patients using the implicit association test.

    Science.gov (United States)

    Park, Jin Young; Ryu, Vin; Ha, Ra Yeon; Lee, Su Jin; Choi, Won-Jung; Ha, Kyooseob; Cho, Hyun-Sang

    2014-04-01

    Although self-esteem is thought to be an important psychological factor in bipolar disorder, little is known about implicit and explicit self-esteem in manic patients. In this study, we investigated differences in implicit and explicit self-esteem among bipolar manic patients, bipolar euthymic patients, and healthy controls using the Implicit Association Test (IAT). Participants included 19 manic patients, 27 euthymic patients, and 27 healthy controls. Participants completed a self-esteem scale to evaluate explicit self-esteem and performed the self-esteem IAT to evaluate implicit self-esteem. There were no differences among groups in explicit self-esteem. However, there were significant differences among groups in implicit self-esteem. Manic patients had higher IAT scores than euthymic patients and a trend toward higher IAT scores than healthy controls. Our findings suggest that, on the latent level, a manic state is not simply the opposite of a depressed state. Furthermore, there may be a discontinuity of implicit self-esteem between manic and euthymic states. These unexpected results may be due to characteristics of the study participants or the methods used to assess implicit self-esteem. Nevertheless, they provide greater insights on the psychological status of manic patients. © 2014.

  7. Collaborative Recurrent Neural Networks forDynamic Recommender Systems

    Science.gov (United States)

    2016-11-22

    JMLR: Workshop and Conference Proceedings 63:366–381, 2016 ACML 2016 Collaborative Recurrent Neural Networks for Dynamic Recommender Systems Young...an unprece- dented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating...Recurrent Neural Network, Recommender System , Neural Language Model, Collaborative Filtering 1. Introduction As ever larger parts of the population

  8. TOURISM RECOMMENDATION SYSTEM: EMPIRICAL INVESTIGATION

    Directory of Open Access Journals (Sweden)

    Biljana PETREVSKA

    2012-12-01

    Full Text Available The paper makes an attempt to justify the necessity of implementing recommendation system which will assist tourists in identification of their ideal holiday. The proposed recommendation system based on collaborative filtering notes positive impulses in the case of Macedonia. A software module is developed being capable to generate a personalized list of favorable and tailor-made items. The research outcomes indicate that the designed national tourism web portal can provide satisfactory performance and may be of high importance to all key-tourism actors in the process of identifying measures necessary for creating competitive tourism product.

  9. A scalable fully implicit framework for reservoir simulation on parallel computers

    KAUST Repository

    Yang, Haijian

    2017-11-10

    The modeling of multiphase fluid flow in porous medium is of interest in the field of reservoir simulation. The promising numerical methods in the literature are mostly based on the explicit or semi-implicit approach, which both have certain stability restrictions on the time step size. In this work, we introduce and study a scalable fully implicit solver for the simulation of two-phase flow in a porous medium with capillarity, gravity and compressibility, which is free from the limitations of the conventional methods. In the fully implicit framework, a mixed finite element method is applied to discretize the model equations for the spatial terms, and the implicit Backward Euler scheme with adaptive time stepping is used for the temporal integration. The resultant nonlinear system arising at each time step is solved in a monolithic way by using a Newton–Krylov type method. The corresponding linear system from the Newton iteration is large sparse, nonsymmetric and ill-conditioned, consequently posing a significant challenge to the fully implicit solver. To address this issue, the family of additive Schwarz preconditioners is taken into account to accelerate the convergence of the linear system, and thereby improves the robustness of the outer Newton method. Several test cases in one, two and three dimensions are used to validate the correctness of the scheme and examine the performance of the newly developed algorithm on parallel computers.

  10. A scalable fully implicit framework for reservoir simulation on parallel computers

    KAUST Repository

    Yang, Haijian; Sun, Shuyu; Li, Yiteng; Yang, Chao

    2017-01-01

    The modeling of multiphase fluid flow in porous medium is of interest in the field of reservoir simulation. The promising numerical methods in the literature are mostly based on the explicit or semi-implicit approach, which both have certain stability restrictions on the time step size. In this work, we introduce and study a scalable fully implicit solver for the simulation of two-phase flow in a porous medium with capillarity, gravity and compressibility, which is free from the limitations of the conventional methods. In the fully implicit framework, a mixed finite element method is applied to discretize the model equations for the spatial terms, and the implicit Backward Euler scheme with adaptive time stepping is used for the temporal integration. The resultant nonlinear system arising at each time step is solved in a monolithic way by using a Newton–Krylov type method. The corresponding linear system from the Newton iteration is large sparse, nonsymmetric and ill-conditioned, consequently posing a significant challenge to the fully implicit solver. To address this issue, the family of additive Schwarz preconditioners is taken into account to accelerate the convergence of the linear system, and thereby improves the robustness of the outer Newton method. Several test cases in one, two and three dimensions are used to validate the correctness of the scheme and examine the performance of the newly developed algorithm on parallel computers.

  11. Training Research: Practical Recommendations for Maximum Impact

    Science.gov (United States)

    Beidas, Rinad S.; Koerner, Kelly; Weingardt, Kenneth R.; Kendall, Philip C.

    2011-01-01

    This review offers practical recommendations regarding research on training in evidence-based practices for mental health and substance abuse treatment. When designing training research, we recommend: (a) aligning with the larger dissemination and implementation literature to consider contextual variables and clearly defining terminology, (b) critically examining the implicit assumptions underlying the stage model of psychotherapy development, (c) incorporating research methods from other disciplines that embrace the principles of formative evaluation and iterative review, and (d) thinking about how technology can be used to take training to scale throughout all stages of a training research project. An example demonstrates the implementation of these recommendations. PMID:21380792

  12. Indonesian News Harvester and Recommender System

    Directory of Open Access Journals (Sweden)

    Adi Wibowo

    2017-09-01

    Full Text Available To provide convenience for the user that frequently read the news, a system to gather, classify, and provide news from several news websites in one place was needed. This system utilized a recommender system to provide only relevant news to the user. This research proposed a system architecture that used vector space model, and Rocchio relevance feedback to provide specific news recommendation to user’s feedback. The results are that the proposed system architecture can achieve the goal by using five levels of feedback from the user. However, the time needed to gather news is increasing exponentially in line with the number of terms gathered from articles.

  13. A point implicit time integration technique for slow transient flow problems

    Energy Technology Data Exchange (ETDEWEB)

    Kadioglu, Samet Y., E-mail: kadioglu@yildiz.edu.tr [Department of Mathematical Engineering, Yildiz Technical University, 34210 Davutpasa-Esenler, Istanbul (Turkey); Berry, Ray A., E-mail: ray.berry@inl.gov [Idaho National Laboratory, P.O. Box 1625, MS 3840, Idaho Falls, ID 83415 (United States); Martineau, Richard C. [Idaho National Laboratory, P.O. Box 1625, MS 3840, Idaho Falls, ID 83415 (United States)

    2015-05-15

    Highlights: • This new method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods. • It is unconditionally stable, as a fully implicit method would be. • It exhibits the simplicity of implementation of an explicit method. • It is specifically designed for slow transient flow problems of long duration such as can occur inside nuclear reactor coolant systems. • Our findings indicate the new method can integrate slow transient problems very efficiently; and its implementation is very robust. - Abstract: We introduce a point implicit time integration technique for slow transient flow problems. The method treats the solution variables of interest (that can be located at cell centers, cell edges, or cell nodes) implicitly and the rest of the information related to same or other variables are handled explicitly. The method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods, except it involves a few additional function(s) evaluation steps. Moreover, the method is unconditionally stable, as a fully implicit method would be. This new approach exhibits the simplicity of implementation of explicit methods and the stability of implicit methods. It is specifically designed for slow transient flow problems of long duration wherein one would like to perform time integrations with very large time steps. Because the method can be time inaccurate for fast transient problems, particularly with larger time steps, an appropriate solution strategy for a problem that evolves from a fast to a slow transient would be to integrate the fast transient with an explicit or semi-implicit technique and then switch to this point implicit method as soon as the time variation slows sufficiently. We have solved several test problems that result from scalar or systems of flow equations. Our findings indicate the new method can integrate slow transient problems very

  14. A point implicit time integration technique for slow transient flow problems

    International Nuclear Information System (INIS)

    Kadioglu, Samet Y.; Berry, Ray A.; Martineau, Richard C.

    2015-01-01

    Highlights: • This new method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods. • It is unconditionally stable, as a fully implicit method would be. • It exhibits the simplicity of implementation of an explicit method. • It is specifically designed for slow transient flow problems of long duration such as can occur inside nuclear reactor coolant systems. • Our findings indicate the new method can integrate slow transient problems very efficiently; and its implementation is very robust. - Abstract: We introduce a point implicit time integration technique for slow transient flow problems. The method treats the solution variables of interest (that can be located at cell centers, cell edges, or cell nodes) implicitly and the rest of the information related to same or other variables are handled explicitly. The method does not require implicit iteration; instead it time advances the solutions in a similar spirit to explicit methods, except it involves a few additional function(s) evaluation steps. Moreover, the method is unconditionally stable, as a fully implicit method would be. This new approach exhibits the simplicity of implementation of explicit methods and the stability of implicit methods. It is specifically designed for slow transient flow problems of long duration wherein one would like to perform time integrations with very large time steps. Because the method can be time inaccurate for fast transient problems, particularly with larger time steps, an appropriate solution strategy for a problem that evolves from a fast to a slow transient would be to integrate the fast transient with an explicit or semi-implicit technique and then switch to this point implicit method as soon as the time variation slows sufficiently. We have solved several test problems that result from scalar or systems of flow equations. Our findings indicate the new method can integrate slow transient problems very

  15. Explicit pre-training instruction does not improve implicit perceptual-motor sequence learning

    OpenAIRE

    Sanchez, Daniel J.; Reber, Paul J.

    2012-01-01

    Memory systems theory argues for separate neural systems supporting implicit and explicit memory in the human brain. Neuropsychological studies support this dissociation, but empirical studies of cognitively healthy participants generally observe that both kinds of memory are acquired to at least some extent, even in implicit learning tasks. A key question is whether this observation reflects parallel intact memory systems or an integrated representation of memory in healthy participants. Lea...

  16. Waveform relaxation methods for implicit differential equations

    NARCIS (Netherlands)

    P.J. van der Houwen; W.A. van der Veen

    1996-01-01

    textabstractWe apply a Runge-Kutta-based waveform relaxation method to initial-value problems for implicit differential equations. In the implementation of such methods, a sequence of nonlinear systems has to be solved iteratively in each step of the integration process. The size of these systems

  17. Implicit Theories of Persuasion.

    Science.gov (United States)

    Roskos-Ewoldsen, David R.

    1997-01-01

    Explores whether individuals have implicit theories of persuasion. Examines how persuasive strategies are cognitively represented--identifies types of tactics in attitude change and social acceptability of persuasive strategies. Finds implicit theories of persuasion reflect the audience's familiarity with the topic. Finds also that implicit…

  18. Privacy-Preserving Content-Based Recommender System

    NARCIS (Netherlands)

    Erkin, Zekeriya; Erkin, Z.; Beye, M.; Veugen, T.; Lagendijk, R.L.

    2012-01-01

    By offering personalized content to users, recommender systems have become a vital tool in e-commerce and online media applications. Content-based algorithms recommend items or products to users, that are most similar to those previously purchased or consumed. Unfortunately, collecting and storing

  19. User Adoption Tendency Modeling for Social Contextual Recommendation

    Directory of Open Access Journals (Sweden)

    Wang Zhisheng

    2015-01-01

    Full Text Available Most of studies on the existing recommender system for Netflix-style sites (scenarios with explicit user feedback focus on rating prediction, but few have systematically analyzed users’ motivations to make decisions on which items to rate. In this paper, the authors study the difficult and challenging task Item Adoption Prediction (IAP for predicting the items users will rate or interact with. It is not only an important supplement to previous works, but also a more realistic requirement of recommendation in this scenario. To recommend the items with high Adoption Tendency, the authors develop a unified model UATM based on the findings of Marketing and Consumer Behavior. The novelty of the model in this paper includes: First, the authors propose a more creative and effective optimization method to tackle One-Class Problem where only the positive feedback is available; second, the authors systematically and conveniently integrate the user adoption information (both explicit and implicit feedbacks included and the social contextual information with quantitatively characterizing different users’ personal sensitivity to various social contextual influences.

  20. The porous boundaries between explicit and implicit memory: behavioral and neural evidence.

    Science.gov (United States)

    Dew, Ilana T Z; Cabeza, Roberto

    2011-04-01

    Explicit memory refers to the conscious retrieval of past information or experiences, whereas implicit memory refers to an unintentional or nonconscious form of retrieval. Much of the literature in cognitive psychology and cognitive neuroscience has focused on differences between explicit and implicit memory, and the traditional view is that they rely on distinct brain systems. However, the potential interplay between implicit and explicit memory is not always clear. This review draws from behavioral and functional neuroimaging evidence to evaluate three areas in which implicit and explicit memory may be interrelated. First, we discuss views of familiarity-based recognition in terms of its relationship with implicit memory. Second, we review the challenges of distinguishing between implicit memory and involuntary aware memory, at both behavioral and neural levels. Finally, we examine evidence indicating that implicit and explicit retrieval of relational information may rely on a common neural mechanism. Taken together, these areas indicate that, under certain circumstances, there may be an important and influential relationship between conscious and nonconscious expressions of memory. © 2011 New York Academy of Sciences.

  1. Lime and fertilizer recommendation system for coconut trees

    Directory of Open Access Journals (Sweden)

    Gustavo Nogueira Guedes Pereira Rosa

    2011-02-01

    Full Text Available Fertilizer recommendation to most agricultural crops is based on response curves. Such curves are constructed from field experimental data, obtained for a particular condition and may not be reliable to be applied to other regions. The aim of this study was to develop a Lime and Fertilizer Recommendation System for Coconut Crop based on the nutritional balance. The System considers the expected productivity and plant nutrient use efficiency to estimate nutrient demand, and effective rooting layer, soil nutrient availability, as well as any other nutrient input to estimate the nutrient supply. Comparing the nutrient demand with the nutrient supply the System defines the nutrient balance. If the balance for a given nutrient is negative, lime and, or, fertilization is recommended. On the other hand, if the balance is positive, no lime or fertilizer is needed. For coconut trees, the fertilization regime is divided in three stages: fertilization at the planting spot, band fertilization and fertilization at the production phase. The data set for the development of the System for coconut trees was obtained from the literature. The recommendations generated by the System were compared to those derived from recommendation tables used for coconut crop in Brazil. The main differences between the two procedures were for the P rate applied in the planting hole, which was higher in the proposed System because the tables do not pay heed to the pit volume, whereas the N and K rates were lower. The crop demand for K is very high, and the rates recommended by the System are superior to the table recommendations for the formation and initial production stage. The fertilizer recommendations by the System are higher for the phase of coconut tree growth as compared to the production phase, because greater amount of biomass is produced in the first phase.

  2. Interpreting Contextual Effects By Contextual Modeling In Recommender Systems

    OpenAIRE

    Zheng, Yong

    2017-01-01

    Recommender systems have been widely applied to assist user's decision making by providing a list of personalized item recommendations. Context-aware recommender systems (CARS) additionally take context information into considering in the recommendation process, since user's tastes on the items may vary from contexts to contexts. Several context-aware recommendation algorithms have been proposed and developed to improve the quality of recommendations. However, there are limited research which...

  3. Explicit versus implicit evaluation to detect inappropriate medication use in geriatric outpatients.

    Science.gov (United States)

    Bahat, Gulistan; Ilhan, Birkan; Bay, Ilker; Kilic, Cihan; Kucukdagli, Pinar; Oren, Meryem Merve; Karan, Mehmet Akif

    2018-04-19

    The rates and reasons why clinicians decide not to follow recommendations from explicit-criteria have been studied scarce. We aimed to compare STOPP version 2 representing one of the most commonly used excplicit tool with the implicit comprehensive geriatric assessment mediated clinical evaluation considered as gold standard. Two hundred and six (n = 206) outpatients ≥65 years old were included. The study was designed as retrospective, cross-sectional, and randomised. STOPP version 2 criteria were systematically used to assess pre-admission treatments followed by implicit clinical evaluation regarding two questions: Were the STOPP criteria recommendations valid for the individual patient and were there any potentially inappropriate-prescription other than depicted by STOPP version 2 criteria? The underlying reason(s) and associated clinical-features were noted. About 62.6% potentially inappropriate-prescriptions were identified (0.6 per-subject) according to systematic application of STOPP v2 while it was 53.4% (0.5 potentially inappropriate-prescriptions per subject) by clinician's application of STOPP v2. Prevalence of non-compliance was 14.7% in 18 (21.7%) of 83 patients identified by systematic application. Suggestion to stop a drug was not accepted because of need of treatment despite likelihood of anticipated side-effects in about 2/3 and with no-anticipated side-effects in about 1/3 of non-compliances. Not following STOPP v2 was significantly associated with lower functional level. According to clinician's implicit-evaluation, there were an extra 59.2% potentially inappropriate-prescriptions (0.6 per subject) in 80 (38.8%) patients yielding a total of 112.6% potentially inappropriate-prescription. Most of the STOPP v2 directed drug cessations are decided valid by the clinicians. In patients with higher functional dependency, it is likely that they are not followed due to palliation focussed care/patient-family preferences. There may be as much as STOPP

  4. An effective collaborative movie recommender system with cuckoo search

    Directory of Open Access Journals (Sweden)

    Rahul Katarya

    2017-07-01

    Full Text Available Recommender systems are information filtering tools that aspire to predict the rating for users and items, predominantly from big data to recommend their likes. Movie recommendation systems provide a mechanism to assist users in classifying users with similar interests. This makes recommender systems essentially a central part of websites and e-commerce applications. This article focuses on the movie recommendation systems whose primary objective is to suggest a recommender system through data clustering and computational intelligence. In this research article, a novel recommender system has been discussed which makes use of k-means clustering by adopting cuckoo search optimization algorithm applied on the Movielens dataset. Our approach has been explained systematically, and the subsequent results have been discussed. It is also compared with existing approaches, and the results have been analyzed and interpreted. Evaluation metrics such as mean absolute error (MAE, standard deviation (SD, root mean square error (RMSE and t-value for the movie recommender system delivers better results as our approach offers lesser value of the mean absolute error, standard deviation, and root mean square error. The experiment results obtained on Movielens dataset stipulate that the proposed approach may provide high performance regarding reliability, efficiency and delivers accurate personalized movie recommendations when compared with existing methods. Our proposed system (K-mean Cuckoo has 0.68 MAE, which is superior to existing work (0.78 MAE [1] and also has improvement of our previous work (0.75 MAE [2].

  5. A fuzzy recommendation system for daily water intake

    Directory of Open Access Journals (Sweden)

    Bin Dai

    2016-05-01

    Full Text Available Water is one of the most important constituents of the human body. Daily consumption of water is thus necessary to protect human health. Daily water consumption is related to several factors such as age, ambient temperature, and degree of physical activity. These factors are generally difficult to express with exact numerical values. The main objective of this article is to build a daily water intake recommendation system using fuzzy methods. This system will use age, physical activity, and ambient temperature as the input factors and daily water intake values as the output factor. The reasoning mechanism of the fuzzy system can calculate the recommended value of daily water intake. Finally, the system will compare the actual recommended values with our system to determine the usefulness. The experimental results show that this recommendation system is effective in actual application.

  6. Towards Geosocial Recommender Systems

    NARCIS (Netherlands)

    de Graaff, V.; van Keulen, Maurice; de By, R.A.; de By, Rolf A.

    2012-01-01

    The usage of social networks sites (SNSs), such as Facebook, and geosocial networks (GSNs), such as Foursquare, has increased tremendously over the past years. The willingness of users to share their current locations and experiences facilitate the creation of geographical recommender systems based

  7. Combined incomplete LU and strongly implicit procedure preconditioning

    Energy Technology Data Exchange (ETDEWEB)

    Meese, E.A. [Univ. of Trondheim (Norway)

    1996-12-31

    For the solution of large sparse linear systems of equations, the Krylov-subspace methods have gained great merit. Their efficiency are, however, largely dependent upon preconditioning of the equation-system. A family of matrix factorisations often used for preconditioning, is obtained from a truncated Gaussian elimination, ILU(p). Less common, supposedly due to it`s restriction to certain sparsity patterns, is factorisations generated by the strongly implicit procedure (SIP). The ideas from ILU(p) and SIP are used in this paper to construct a generalized strongly implicit procedure, applicable to matrices with any sparsity pattern. The new algorithm has been run on some test equations, and efficiency improvements over ILU(p) was found.

  8. A Transitive Recommendation System for Information Technology Communities

    Directory of Open Access Journals (Sweden)

    Hesham Ali

    2013-06-01

    Full Text Available Social networks have become a new trend for research among computer scientist around the world. Social network had an impact on users' way of life. One of social network usages is recommendation systems. The need of recommendation systems is arising when users try to know best choice for them in many items types (books, experts, locations, technologies...etc. The problem is that a single person can't try all alternatives in all possibles life goals to compare. Thus, a person has to use his friends' expertise to select better option in any item category. This process is the main idea of “Recommendation Systems”. Recommendation systems usually depend on users-to-items ratings in a network (graph. Two main challenges for recommendation systems are accuracy of recommendation and computation size. The main objective of this paper is to introduce a suggested technique for transitive recommendation system based on users' collaborative ratings, and also to balance loading of computation. All this has to be applied on a special type of social network. Our work studied the transitivity usage in connections to get a relation (path as a recommendation for nodes not directly connected. The target social network has eight types of nodes. So, there are techniques that are not suitable to this complex type of network. Those we can present a new support for recommending items of several types to users with several types. We believe that this functionality hasn't been fully provided elsewhere. We have suggested using single source shortest path algorithm combined with Map Reduce technique, and mathematically deduced that we have a speeding up of algorithm by 10% approximately. Our testing results shows an accuracy of 89% and false rejection of 99% compared to traditional algorithms with less configuration parameters and more steady count of recommendations.

  9. The neural basis of implicit learning and memory: a review of neuropsychological and neuroimaging research.

    Science.gov (United States)

    Reber, Paul J

    2013-08-01

    Memory systems research has typically described the different types of long-term memory in the brain as either declarative versus non-declarative or implicit versus explicit. These descriptions reflect the difference between declarative, conscious, and explicit memory that is dependent on the medial temporal lobe (MTL) memory system, and all other expressions of learning and memory. The other type of memory is generally defined by an absence: either the lack of dependence on the MTL memory system (nondeclarative) or the lack of conscious awareness of the information acquired (implicit). However, definition by absence is inherently underspecified and leaves open questions of how this type of memory operates, its neural basis, and how it differs from explicit, declarative memory. Drawing on a variety of studies of implicit learning that have attempted to identify the neural correlates of implicit learning using functional neuroimaging and neuropsychology, a theory of implicit memory is presented that describes it as a form of general plasticity within processing networks that adaptively improve function via experience. Under this model, implicit memory will not appear as a single, coherent, alternative memory system but will instead be manifested as a principle of improvement from experience based on widespread mechanisms of cortical plasticity. The implications of this characterization for understanding the role of implicit learning in complex cognitive processes and the effects of interactions between types of memory will be discussed for examples within and outside the psychology laboratory. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. Transient subchannel simulation of sodium boiling in a 37 rods bundle with semi implicit and full implicit algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Azad, Hamed Moslehi; Shirani, A.S. [Shahid Beheshti Univ., Tehran (Iran, Islamic Republic of). Dept. of Nuclear Engineering

    2017-07-15

    Thermal hydraulic analysis of sodium boiling in fuel assemblies is an important issue in safety of sodium cooled reactors and subchannel method is an efficient approach in transient two phase flow analyses. Almost all of the subchannel codes which use two-fluid model in two phase flow analysis, are based on semi implicit algorithm. With the full implicit method it is possible to use larger time steps. In order to compare the semi implicit algorithm with full implicit algorithm, two transient subchannel numerical programs which one is based on semi implicit algorithm and the other is based on full implicit algorithm have been written in FORTRAN in this work for simulation of transients in sodium cooled Kompakter-Natriumsiede-Kreislauf (KNS) at the former Kernforschungszentrum Karlsruhe (KfK) in Germany.

  11. Implicit false-belief processing in the human brain.

    Science.gov (United States)

    Schneider, Dana; Slaughter, Virginia P; Becker, Stefanie I; Dux, Paul E

    2014-11-01

    Eye-movement patterns in 'Sally-Anne' tasks reflect humans' ability to implicitly process the mental states of others, particularly false-beliefs - a key theory of mind (ToM) operation. It has recently been proposed that an efficient ToM system, which operates in the absence of awareness (implicit ToM, iToM), subserves the analysis of belief-like states. This contrasts to consciously available belief processing, performed by the explicit ToM system (eToM). The frontal, temporal and parietal cortices are engaged when humans explicitly 'mentalize' about others' beliefs. However, the neural underpinnings of implicit false-belief processing and the extent to which they draw on networks involved in explicit general-belief processing are unknown. Here, participants watched 'Sally-Anne' movies while fMRI and eye-tracking measures were acquired simultaneously. Participants displayed eye-movements consistent with implicit false-belief processing. After independently localizing the brain areas involved in explicit general-belief processing, only the left anterior superior temporal sulcus and precuneus revealed greater blood-oxygen-level-dependent activity for false- relative to true-belief trials in our iToM paradigm. No such difference was found for the right temporal-parietal junction despite significant activity in this area. These findings fractionate brain regions that are associated with explicit general ToM reasoning and false-belief processing in the absence of awareness. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. An effect of age on implicit memory that is not due to explicit contamination: implications for single and multiple-systems theories.

    Science.gov (United States)

    Ward, Emma V; Berry, Christopher J; Shanks, David R

    2013-06-01

    Recognition memory is typically weaker in healthy older relative to young adults, while performance on implicit tests (e.g., repetition priming) is often comparable between groups. Such observations are commonly taken as evidence for independent explicit and implicit memory systems. On a picture version of the continuous identification with recognition (CID-R) task, we found a reliable age-related reduction in recognition memory, while the age effect on priming did not reach statistical significance (Experiment 1). This pattern was consistent with the predictions of a formal single-system model. Experiment 2 replicated these observations using separate priming (continuous identification; CID) and recognition phases, while a combined data analysis revealed a significant effect of age on priming. In Experiment 3, we provide evidence that priming in this task is unaffected by explicit processing, and we conclude that the age difference in priming is unlikely to have been driven by differences in explicit processing between groups of young and older adults ("explicit contamination"). The results support the view that explicit and implicit expressions of memory are driven by a single underlying memory system. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  13. Non-IID Recommender Systems: A Review and Framework of Recommendation Paradigm Shifting

    Directory of Open Access Journals (Sweden)

    Longbing Cao

    2016-06-01

    Full Text Available While recommendation plays an increasingly critical role in our living, study, work, and entertainment, the recommendations we receive are often for irrelevant, duplicate, or uninteresting products and services. A critical reason for such bad recommendations lies in the intrinsic assumption that recommended users and items are independent and identically distributed (IID in existing theories and systems. Another phenomenon is that, while tremendous efforts have been made to model specific aspects of users or items, the overall user and item characteristics and their non-IIDness have been overlooked. In this paper, the non-IID nature and characteristics of recommendation are discussed, followed by the non-IID theoretical framework in order to build a deep and comprehensive understanding of the intrinsic nature of recommendation problems, from the perspective of both couplings and heterogeneity. This non-IID recommendation research triggers the paradigm shift from IID to non-IID recommendation research and can hopefully deliver informed, relevant, personalized, and actionable recommendations. It creates exciting new directions and fundamental solutions to address various complexities including cold-start, sparse data-based, cross-domain, group-based, and shilling attack-related issues.

  14. Creating adaptive web recommendation system based on user behavior

    Science.gov (United States)

    Walek, Bogdan

    2018-01-01

    The paper proposes adaptive web recommendation system based on user behavior. The proposed system uses expert system to evaluating and recommending suitable items of content. Relevant items are subsequently evaluated and filtered based on history of visited items and user´s preferred categories of items. Main parts of the proposed system are presented and described. The proposed recommendation system is verified on specific example.

  15. Implicit solvers for large-scale nonlinear problems

    International Nuclear Information System (INIS)

    Keyes, David E; Reynolds, Daniel R; Woodward, Carol S

    2006-01-01

    Computational scientists are grappling with increasingly complex, multi-rate applications that couple such physical phenomena as fluid dynamics, electromagnetics, radiation transport, chemical and nuclear reactions, and wave and material propagation in inhomogeneous media. Parallel computers with large storage capacities are paving the way for high-resolution simulations of coupled problems; however, hardware improvements alone will not prove enough to enable simulations based on brute-force algorithmic approaches. To accurately capture nonlinear couplings between dynamically relevant phenomena, often while stepping over rapid adjustments to quasi-equilibria, simulation scientists are increasingly turning to implicit formulations that require a discrete nonlinear system to be solved for each time step or steady state solution. Recent advances in iterative methods have made fully implicit formulations a viable option for solution of these large-scale problems. In this paper, we overview one of the most effective iterative methods, Newton-Krylov, for nonlinear systems and point to software packages with its implementation. We illustrate the method with an example from magnetically confined plasma fusion and briefly survey other areas in which implicit methods have bestowed important advantages, such as allowing high-order temporal integration and providing a pathway to sensitivity analyses and optimization. Lastly, we overview algorithm extensions under development motivated by current SciDAC applications

  16. Predictive Validity of Explicit and Implicit Threat Overestimation in Contamination Fear

    Science.gov (United States)

    Green, Jennifer S.; Teachman, Bethany A.

    2012-01-01

    We examined the predictive validity of explicit and implicit measures of threat overestimation in relation to contamination-fear outcomes using structural equation modeling. Undergraduate students high in contamination fear (N = 56) completed explicit measures of contamination threat likelihood and severity, as well as looming vulnerability cognitions, in addition to an implicit measure of danger associations with potential contaminants. Participants also completed measures of contamination-fear symptoms, as well as subjective distress and avoidance during a behavioral avoidance task, and state looming vulnerability cognitions during an exposure task. The latent explicit (but not implicit) threat overestimation variable was a significant and unique predictor of contamination fear symptoms and self-reported affective and cognitive facets of contamination fear. On the contrary, the implicit (but not explicit) latent measure predicted behavioral avoidance (at the level of a trend). Results are discussed in terms of differential predictive validity of implicit versus explicit markers of threat processing and multiple fear response systems. PMID:24073390

  17. A Group Recommender System for Tourist Activities

    Science.gov (United States)

    Garcia, Inma; Sebastia, Laura; Onaindia, Eva; Guzman, Cesar

    This paper introduces a method for giving recommendations of tourist activities to a group of users. This method makes recommendations based on the group tastes, their demographic classification and the places visited by the users in former trips. The group recommendation is computed from individual personal recommendations through the use of techniques such as aggregation, intersection or incremental intersection. This method is implemented as an extension of the e-Tourism tool, which is a user-adapted tourism and leisure application, whose main component is the Generalist Recommender System Kernel (GRSK), a domain-independent taxonomy-driven search engine that manages the group recommendation.

  18. Unconditionally Energy Stable Implicit Time Integration: Application to Multibody System Analysis and Design

    DEFF Research Database (Denmark)

    Chen, Shanshin; Tortorelli, Daniel A.; Hansen, John Michael

    1999-01-01

    of ordinary diffferential equations is employed to avoid the instabilities associated with the direct integrations of differential-algebraic equations. To extend the unconditional stability of the implicit Newmark method to nonlinear dynamic systems, a discrete energy balance is enforced. This constraint......Advances in computer hardware and improved algorithms for multibody dynamics over the past decade have generated widespread interest in real-time simulations of multibody mechanics systems. At the heart of the widely used algorithms for multibody dynamics are a choice of coordinates which define...... the kinmatics of the system, and a choice of time integrations algorithms. The current approach uses a non-dissipative implict Newmark method to integrate the equations of motion defined in terms of the independent joint coordinates of the system. The reduction of the equations of motion to a minimal set...

  19. Online evaluation of point-of-interest recommendation systems

    NARCIS (Netherlands)

    Dean-Hall, A.; Clarke, C.L.A.; Kamps, J.; Kiseleva, J.

    2015-01-01

    In this work we describe a system to evaluate multiple point- of-interest recommendation systems. In this system each recommendation service will be exposed online and crowd-sourced assessors will interact with merged results from multiple services, which are responding to suggestion requests live,

  20. Privacy enhanced recommender system

    NARCIS (Netherlands)

    Erkin, Zekeriya; Erkin, Zekeriya; Beye, Michael; Veugen, Thijs; Lagendijk, Reginald L.

    2010-01-01

    Recommender systems are widely used in online applications since they enable personalized service to the users. The underlying collaborative filtering techniques work on user’s data which are mostly privacy sensitive and can be misused by the service provider. To protect the privacy of the users, we

  1. Useful and usable alarm systems : recommended properties

    International Nuclear Information System (INIS)

    Veland, Oeystein; Kaarstad, Magnhild; Seim, Lars Aage; Foerdestroemmen, Nils T.

    2001-01-01

    This document describes the result of a study on alarm systems conducted by IFE in Halden. The study was initiated by the Norwegian Petroleum Directorate. The objective was to identify and formulate a set of important properties for useful and usable alarm systems. The study is mainly based on review of the latest international recognised guidelines and standards on alarm systems available at the time of writing, with focus on realistic solutions from research and best practice from different industries. In addition, IFE experiences gathered through specification and design of alarm systems and experimental activities in HAMMLAB and bilateral projects, have been utilized where relevant. The document presents a total of 43 recommendations divided into a number of general recommendations and more detailed recommendations on alarm generation, structuring, prioritisation, presentation and handling. (Author)

  2. Implicit and fully implicit exponential finite difference methods

    Indian Academy of Sciences (India)

    Burgers' equation; exponential finite difference method; implicit exponential finite difference method; ... This paper describes two new techniques which give improved exponential finite difference solutions of Burgers' equation. ... Current Issue

  3. Implicit self-stigma in people with mental illness.

    Science.gov (United States)

    Rüsch, Nicolas; Corrigan, Patrick W; Todd, Andrew R; Bodenhausen, Galen V

    2010-02-01

    People with mental illness often internalize negative stereotypes, resulting in self-stigma and low self-esteem ("People with mental illness are bad and therefore I am bad, too"). Despite strong evidence for self-stigma's negative impact as assessed by self-report measures, it is unclear whether self-stigma operates in an automatic, implicit manner, potentially outside conscious awareness and control. We therefore assessed (i) negative implicit attitudes toward mental illness and (ii) low implicit self-esteem using 2 Brief Implicit Association Tests in 85 people with mental illness. Implicit self-stigma was operationalized as the product of both implicit measures. Explicit self-stigma and quality of life were assessed by self-report. Greater implicit and explicit self-stigma independently predicted lower quality of life after controlling for depressive symptoms, diagnosis, and demographic variables. Our results suggest that implicit self-stigma is a measurable construct and is associated with negative outcomes. Attempts to reduce self-stigma should take implicit processes into account.

  4. Comparing Explicit and Implicit Learning of Emotional and Non-Emotional Words in Autistic Children

    Directory of Open Access Journals (Sweden)

    Vahid Nejati

    2013-02-01

    Full Text Available Background: Explicit and implicit memories have different cerebral origins and learning approaches. Defective emotional words processing in children with autism may affect the memory allocated to such words. The aim of this study was comparing two types of (explicit and implicit memories during processing the two types of (emotional and non-emotional words in autistic children and their healthy counterparts. Materials and Methods: The present cross sectional study was conducted on 14 autistic children, who had referred to Autism Medical Treatment Center on Tehran, and 14 healthy children in kindergartens and schools across Tehran. For the explicit memory, a list of words was presented to the subjects of our study and they were asked to repeat the words they heard one time immediately and one time with delay. For implicit memory, the subjects were asked to identify the heard words among the presented words. Statistical analysis was performed using two-way analysis of variance. Results: The results showed that the normal children have higher efficiency in explicit and implicit memory than the children with autism (p<0.01. The two-way analysis of memory type and word type showed that the former affects memory significantly (p<0.05 while word type had no significant effect. Conclusion: Autistic children suffer from impaired memory. This defect is higher in implicit memory than in the explicit memory. It is recommended to apply rehabilitation, training, learning approaches and also explicit memory for interventions of autistic children.

  5. TDCCREC: AN EFFICIENT AND SCALABLE WEB-BASED RECOMMENDATION SYSTEM

    Directory of Open Access Journals (Sweden)

    K.Latha

    2010-10-01

    Full Text Available Web browsers are provided with complex information space where the volume of information available to them is huge. There comes the Recommender system which effectively recommends web pages that are related to the current webpage, to provide the user with further customized reading material. To enhance the performance of the recommender systems, we include an elegant proposed web based recommendation system; Truth Discovery based Content and Collaborative RECommender (TDCCREC which is capable of addressing scalability. Existing approaches such as Learning automata deals with usage and navigational patterns of users. On the other hand, Weighted Association Rule is applied for recommending web pages by assigning weights to each page in all the transactions. Both of them have their own disadvantages. The websites recommended by the search engines have no guarantee for information correctness and often delivers conflicting information. To solve them, content based filtering and collaborative filtering techniques are introduced for recommending web pages to the active user along with the trustworthiness of the website and confidence of facts which outperforms the existing methods. Our results show how the proposed recommender system performs better in predicting the next request of web users.

  6. Machine learning paradigms applications in recommender systems

    CERN Document Server

    Lampropoulos, Aristomenis S

    2015-01-01

    This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and ...

  7. Functional imaging of implicit marijuana associations during performance on an Implicit Association Test (IAT)

    NARCIS (Netherlands)

    Ames, S.L.; Grenard, J.L.; Stacy, A.W.; Xiao, L.; He, Q.; Wong, S.W; Xue, G.; Wiers, R.W.; Bechara, A.

    2013-01-01

    This research evaluated the neural correlates of implicit associative memory processes (habit-based processes) through the imaging (fMRI) of a marijuana Implicit Association Test. Drug-related associative memory effects have been shown to consistently predict level of drug use. To observe

  8. Improving electronic customers' profile in recommender systems using data mining techniques

    Directory of Open Access Journals (Sweden)

    Mohammad Julashokri

    2011-10-01

    Full Text Available Recommender systems are tools for realization one to one marketing. Recommender systems are systems, which attract, retain, and develop customers. Recommender systems use several ways to make recommendations. Two ways are using more than the others: collaborative filtering and content-based filtering. In this study, a recommender system model based on collaborative filtering has proposed. Proposed model was endeavored to improve the customer profile in collaborative systems to enhance the recommender system efficiency. This improvement was done using time context and group preferences. Experimental results show that the proposed model has a better recommendation performance than existing models.

  9. A Literature Review on Recommender Systems Algorithms, Techniques and Evaluations

    Directory of Open Access Journals (Sweden)

    Kasra Madadipouya

    2017-07-01

    Full Text Available One of the most crucial issues, nowadays, is to provide personalized services to each individual based on their preferences. To achieve this goal, recommender system could be utilized as a tool to help the users in decision-making process offering different items and options. They are utilized to predict and recommend relevant items to end users. In this case an item could be anything such as a document, a location, a movie, an article or even a user (friend suggestion. The main objective of the recommender systems is to suggest items which have great potential to be liked by users. In modern recommender systems, various methods are combined together with the aim of extracting patterns in available datasets. Combination of different algorithms make prediction more convoluted since various parameters should be taken into account in providing recommendations. Recommendations could be personalized or non-personalized. In non-personalized type, selection of the items for a user is based on the number of the times that an item has been visited in the past by other users. However, in the personalized type, the main objective is to provide the best items to the user based on her taste and preferences. Although, in many domains recommender systems gained significant improvements and provide better services for users, it still requires further research to improve accuracy of recommendations in many aspects. In fact, the current available recommender systems are far from the ideal model of the recommender system. This paper reviews state of art in recommender systems algorithms and techniques which is necessary to identify the gaps and improvement areas. In addition to that, we provide possible solutions to overcome shortages and known issues of recommender systems as well as discussing about recommender systems evaluation methods and metrics in details.

  10. Recommender Systems for the Social Web

    CERN Document Server

    Pazos Arias, José J; Díaz Redondo, Rebeca P

    2012-01-01

    The recommendation of products, content and services cannot be considered newly born, although its widespread application is still in full swing. While its growing success in numerous sectors, the progress of the  Social Web has revolutionized the architecture of participation and relationship in the Web, making it necessary to restate recommendation and reconciling it with Collaborative Tagging, as the popularization of authoring in the Web, and  Social Networking, as the translation of personal relationships to the Web. Precisely, the convergence of recommendation with the above Social Web pillars is what motivates this book, which has collected contributions from well-known experts in the academy and the industry to provide a broader view of the problems that Social Recommenders might face with.  If recommender systems have proven their key role in facilitating the user access to resources on the Web, when sharing resources has become social, it is natural for recommendation strategies in the Social Web...

  11. Recommender systems for location-based social networks

    CERN Document Server

    Symeonidis, Panagiotis; Manolopoulos, Yannis

    2014-01-01

    Online social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc.) to provide them with recommendations of new products or friends. Lately, technological progressions in mobile devices (i.e. smart phones) enabled the incorporation of geo-location data in the traditional web-based online social networks, bringing the new era of Social and Mobile Web. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving Location-based Social Networks (LBSNs). The chapters introduce a wide variety of recent approaches, from the most basic to the state-of-the-art, for providing recommendations in LBSNs. The book is organized into three parts. Part 1 provides introductory material on recommender systems, online social networks and LBSNs. Part 2 presents a wide variety of recommendation algorithms, ranging from basic to cutting edge, as well as a comparison of the characteristics of t...

  12. Block Preconditioning to Enable Physics-Compatible Implicit Multifluid Plasma Simulations

    Science.gov (United States)

    Phillips, Edward; Shadid, John; Cyr, Eric; Miller, Sean

    2017-10-01

    Multifluid plasma simulations involve large systems of partial differential equations in which many time-scales ranging over many orders of magnitude arise. Since the fastest of these time-scales may set a restrictively small time-step limit for explicit methods, the use of implicit or implicit-explicit time integrators can be more tractable for obtaining dynamics at time-scales of interest. Furthermore, to enforce properties such as charge conservation and divergence-free magnetic field, mixed discretizations using volume, nodal, edge-based, and face-based degrees of freedom are often employed in some form. Together with the presence of stiff modes due to integrating over fast time-scales, the mixed discretization makes the required linear solves for implicit methods particularly difficult for black box and monolithic solvers. This work presents a block preconditioning strategy for multifluid plasma systems that segregates the linear system based on discretization type and approximates off-diagonal coupling in block diagonal Schur complement operators. By employing multilevel methods for the block diagonal subsolves, this strategy yields algorithmic and parallel scalability which we demonstrate on a range of problems.

  13. A Top-N Recommender System Evaluation Protocol Inspired by Deployed Systems

    NARCIS (Netherlands)

    A. Said (Alan); A. Bellogín Kouki (Alejandro); A.P. de Vries (Arjen)

    2013-01-01

    htmlabstractThe evaluation of recommender systems is crucial for their development. In today's recommendation landscape there are many standardized recommendation algorithms and approaches, however, there exists no standardized method for experimental setup of evaluation -- not even for widely used

  14. Multilevel hybrid split-step implicit tau-leap

    KAUST Repository

    Ben Hammouda, Chiheb

    2016-06-17

    In biochemically reactive systems with small copy numbers of one or more reactant molecules, the dynamics is dominated by stochastic effects. To approximate those systems, discrete state-space and stochastic simulation approaches have been shown to be more relevant than continuous state-space and deterministic ones. In systems characterized by having simultaneously fast and slow timescales, existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap (explicit-TL) method, can be very slow. Implicit approximations have been developed to improve numerical stability and provide efficient simulation algorithms for those systems. Here, we propose an efficient Multilevel Monte Carlo (MLMC) method in the spirit of the work by Anderson and Higham (SIAM Multiscal Model. Simul. 10(1), 2012). This method uses split-step implicit tau-leap (SSI-TL) at levels where the explicit-TL method is not applicable due to numerical stability issues. We present numerical examples that illustrate the performance of the proposed method. © 2016 Springer Science+Business Media New York

  15. A Sentiment-Enhanced Hybrid Recommender System for Movie Recommendation: A Big Data Analytics Framework

    OpenAIRE

    Wang, Yibo; Wang, Mingming; Xu, Wei

    2018-01-01

    Movie recommendation in mobile environment is critically important for mobile users. It carries out comprehensive aggregation of user’s preferences, reviews, and emotions to help them find suitable movies conveniently. However, it requires both accuracy and timeliness. In this paper, a movie recommendation framework based on a hybrid recommendation model and sentiment analysis on Spark platform is proposed to improve the accuracy and timeliness of mobile movie recommender system. In the propo...

  16. Data Mining Methods for Recommender Systems

    Science.gov (United States)

    Amatriain, Xavier; Jaimes*, Alejandro; Oliver, Nuria; Pujol, Josep M.

    In this chapter, we give an overview of the main Data Mining techniques used in the context of Recommender Systems. We first describe common preprocessing methods such as sampling or dimensionality reduction. Next, we review the most important classification techniques, including Bayesian Networks and Support Vector Machines. We describe the k-means clustering algorithm and discuss several alternatives. We also present association rules and related algorithms for an efficient training process. In addition to introducing these techniques, we survey their uses in Recommender Systems and present cases where they have been successfully applied.

  17. A Federated Recommender System for Online Learning Environments

    OpenAIRE

    Zhou, Lei; El Helou, Sandy; Moccozet, Laurent; Opprecht, Laurent; Benkacem, Omar; Salzmann, Christophe; Gillet, Denis

    2012-01-01

    From e-commerce to social networking sites, recommender systems are gaining more and more interest. They provide connections, news, resources, or products of interest. This paper presents a federated recommender system, which exploits data from different online learning platforms and delivers personalized recommendation. The underlying educational objective is to enable academic institutions to provide a Web 2.0 dashboard bringing together open resources from the Cloud and proprietary content...

  18. Deployment of Recommender Systems: Operational and Strategic Issues

    Science.gov (United States)

    Ghoshal, Abhijeet

    2011-01-01

    E-commerce firms are increasingly adopting recommendation systems to effectively target customers with products and services. The first essay examines the impact that improving a recommender system has on firms that deploy such systems. A market with customers heterogeneous in their search costs is considered. We find that in a monopoly, a firm…

  19. Solving the stability-accuracy-diversity dilemma of recommender systems

    Science.gov (United States)

    Hou, Lei; Liu, Kecheng; Liu, Jianguo; Zhang, Runtong

    2017-02-01

    Recommender systems are of great significance in predicting the potential interesting items based on the target user's historical selections. However, the recommendation list for a specific user has been found changing vastly when the system changes, due to the unstable quantification of item similarities, which is defined as the recommendation stability problem. To improve the similarity stability and recommendation stability is crucial for the user experience enhancement and the better understanding of user interests. While the stability as well as accuracy of recommendation could be guaranteed by recommending only popular items, studies have been addressing the necessity of diversity which requires the system to recommend unpopular items. By ranking the similarities in terms of stability and considering only the most stable ones, we present a top- n-stability method based on the Heat Conduction algorithm (denoted as TNS-HC henceforth) for solving the stability-accuracy-diversity dilemma. Experiments on four benchmark data sets indicate that the TNS-HC algorithm could significantly improve the recommendation stability and accuracy simultaneously and still retain the high-diversity nature of the Heat Conduction algorithm. Furthermore, we compare the performance of the TNS-HC algorithm with a number of benchmark recommendation algorithms. The result suggests that the TNS-HC algorithm is more efficient in solving the stability-accuracy-diversity triple dilemma of recommender systems.

  20. Research and Design of a Grid Based Electronic Commerce Recommendation System

    OpenAIRE

    Liang, Yueling; Nie, Guihua

    2010-01-01

    Current electronic commerce recommendation system is designed for single electronic commerce website and current recommendation technologies have obvious deficiencies Centralized recommendation systems can not resolve the contradiction between high recommendation quality and timely response, as well as that between limited recommendation range and ever rich information on the web. Distributed recommendation systems are expected to improve the recommendation quality while maintaining high perf...

  1. Marketing Recommender Systems: A New Approach in Digital Economy

    Directory of Open Access Journals (Sweden)

    Loredana MOCEAN

    2012-01-01

    Full Text Available Marketing information systems are those systems which make the gathering, processing, selection, storage, transmission and display of coordinated and continuous internal and external information. Includes systematic and formal methods used for managing all of an organization's information market. Recommendation systems are those systems that are widely used in online systems to suggest items that users might find interesting. These recommendations are generated using in particular two techniques: content-based and collaborative filtering. This paper aims to define a new system, namely Marketing Recommender System, a system that serves marketing and uses techniques and methods of the digital economy.

  2. Implicit Attitudes Toward Green Consumer Behaviour

    Directory of Open Access Journals (Sweden)

    Delphine Vantomme

    2005-12-01

    Full Text Available The purpose of this study was to examine the usefulness of implicit (automatic attitudes to explain the weak attitude-behaviour relationships often found in green consumer behaviour research. Therefore, not only explicit but also implicit attitudes toward green consumer behaviour were measured by means of the Implicit Association Test (IAT. Explicit measures revealed positive attitudes, while the IAT showed more positive attitudes toward the ecological than toward the traditional product (Experiment 1 or no differences in these attitudes (Experiment 2 and follow-up study. When existing products were involved, implicit attitudes related to behavioural intention, even where the explicit attitude measure did not.

  3. Overweight people have low levels of implicit weight bias, but overweight nations have high levels of implicit weight bias.

    Directory of Open Access Journals (Sweden)

    Maddalena Marini

    Full Text Available Although a greater degree of personal obesity is associated with weaker negativity toward overweight people on both explicit (i.e., self-report and implicit (i.e., indirect behavioral measures, overweight people still prefer thin people on average. We investigated whether the national and cultural context - particularly the national prevalence of obesity - predicts attitudes toward overweight people independent of personal identity and weight status. Data were collected from a total sample of 338,121 citizens from 71 nations in 22 different languages on the Project Implicit website (https://implicit.harvard.edu/ between May 2006 and October 2010. We investigated the relationship of the explicit and implicit weight bias with the obesity both at the individual (i.e., across individuals and national (i.e., across nations level. Explicit weight bias was assessed with self-reported preference between overweight and thin people; implicit weight bias was measured with the Implicit Association Test (IAT. The national estimates of explicit and implicit weight bias were obtained by averaging the individual scores for each nation. Obesity at the individual level was defined as Body Mass Index (BMI scores, whereas obesity at the national level was defined as three national weight indicators (national BMI, national percentage of overweight and underweight people obtained from publicly available databases. Across individuals, greater degree of obesity was associated with weaker implicit negativity toward overweight people compared to thin people. Across nations, in contrast, a greater degree of national obesity was associated with stronger implicit negativity toward overweight people compared to thin people. This result indicates a different relationship between obesity and implicit weight bias at the individual and national levels.

  4. Recommendation Report: EJournals/EBooks A-Z Management System

    KAUST Repository

    Ramli, Rindra M.

    2014-01-01

    This is a recommendation report for KAUST Library on the Ejournals / EBooks AZ Management systems project. It briefly described the issues faced by the ERM Team, project plan overview and the project findings as well as the recommendation(s).

  5. CitRec 2017 : International Workshop on Recommender Systems for Citizens

    NARCIS (Netherlands)

    Yang, J.; Sun, Zhu; Bozzon, A.; Zhang, J.; Larson, M.A.

    2017-01-01

    The "International Workshop on Recommender Systems for Citizens" (CitRec) is focused on a novel type of recommender systems both in terms of ownership and purpose: recommender systems run by citizens and serving society as a whole.

  6. Moderators of Implicit-Explicit Exercise Cognition Concordance.

    Science.gov (United States)

    Berry, Tanya R; Rodgers, Wendy M; Markland, David; Hall, Craig R

    2016-12-01

    Investigating implicit-explicit concordance can aid in understanding underlying mechanisms and possible intervention effects. This research examined the concordance between implicit associations of exercise with health or appearance and related explicit motives. Variables considered as possible moderators were behavioral regulations, explicit attitudes, and social desirability. Participants (N = 454) completed measures of implicit associations of exercise with health and appearance and questionnaire measures of health and appearance motives, attitudes, social desirability, and behavioral regulations. Attitudes significantly moderated the relationship between implicit associations of exercise with health and health motives. Identified regulations significantly moderated implicit-explicit concordance with respect to associations with appearance. These results suggest that implicit and explicit exercise-related cognitions are not necessarily independent and their relationship to each other may be moderated by attitudes or some forms of behavioral regulation. Future research that takes a dual-processing approach to exercise behavior should consider potential theoretical moderators of concordance.

  7. Using the Implicit Association Test to Assess Children's Implicit Attitudes toward Smoking

    OpenAIRE

    Andrews, Judy A.; Hampson, Sarah E.; Greenwald, Anthony G.; Gordon, Judith; Widdop, Chris

    2010-01-01

    The development and psychometric properties of an Implicit Association Test (IAT) measuring implicit attitude toward smoking among fifth grade children were described. The IAT with “sweets” as the contrast category resulted in higher correlations with explicit attitudes than did the IAT with “healthy foods” as the contrast category. Children with family members who smoked (versus non-smoking) and children who were high in sensation seeking (versus low) had a significantly more favorable impli...

  8. Implicit and explicit attitudes towards conventional and complementary and alternative medicine treatments: Introduction of an Implicit Association Test.

    Science.gov (United States)

    Green, James A; Hohmann, Cynthia; Lister, Kelsi; Albertyn, Riani; Bradshaw, Renee; Johnson, Christine

    2016-06-01

    This study examined associations between anticipated future health behaviour and participants' attitudes. Three Implicit Association Tests were developed to assess safety, efficacy and overall attitude. They were used to examine preference associations between conventional versus complementary and alternative medicine among 186 participants. A structural equation model suggested only a single implicit association, rather than three separate domains. However, this single implicit association predicted additional variance in anticipated future use of complementary and alternative medicine beyond explicit. Implicit measures should give further insight into motivation for complementary and alternative medicine use. © The Author(s) 2014.

  9. DRARS, A Dynamic Risk-Aware Recommender System

    OpenAIRE

    Bouneffouf , Djallel

    2013-01-01

    The vast amount of information generated and maintained everyday by information systems and their users leads to the increasingly important concern of overload information. In this context, traditional recommender systems provide relevant information to the users. Nevertheless, with the recent dissemination of mobile devices (smartphones and tablets), there is a gradual user migration to the use of pervasive computing environments. The problem with the traditional recommendation approaches is...

  10. Multigrid treatment of implicit continuum diffusion

    Science.gov (United States)

    Francisquez, Manaure; Zhu, Ben; Rogers, Barrett

    2017-10-01

    Implicit treatment of diffusive terms of various differential orders common in continuum mechanics modeling, such as computational fluid dynamics, is investigated with spectral and multigrid algorithms in non-periodic 2D domains. In doubly periodic time dependent problems these terms can be efficiently and implicitly handled by spectral methods, but in non-periodic systems solved with distributed memory parallel computing and 2D domain decomposition, this efficiency is lost for large numbers of processors. We built and present here a multigrid algorithm for these types of problems which outperforms a spectral solution that employs the highly optimized FFTW library. This multigrid algorithm is not only suitable for high performance computing but may also be able to efficiently treat implicit diffusion of arbitrary order by introducing auxiliary equations of lower order. We test these solvers for fourth and sixth order diffusion with idealized harmonic test functions as well as a turbulent 2D magnetohydrodynamic simulation. It is also shown that an anisotropic operator without cross-terms can improve model accuracy and speed, and we examine the impact that the various diffusion operators have on the energy, the enstrophy, and the qualitative aspect of a simulation. This work was supported by DOE-SC-0010508. This research used resources of the National Energy Research Scientific Computing Center (NERSC).

  11. Hybrid attacks on model-based social recommender systems

    Science.gov (United States)

    Yu, Junliang; Gao, Min; Rong, Wenge; Li, Wentao; Xiong, Qingyu; Wen, Junhao

    2017-10-01

    With the growing popularity of the online social platform, the social network based approaches to recommendation emerged. However, because of the open nature of rating systems and social networks, the social recommender systems are susceptible to malicious attacks. In this paper, we present a certain novel attack, which inherits characteristics of the rating attack and the relation attack, and term it hybrid attack. Furtherly, we explore the impact of the hybrid attack on model-based social recommender systems in multiple aspects. The experimental results show that, the hybrid attack is more destructive than the rating attack in most cases. In addition, users and items with fewer ratings will be influenced more when attacked. Last but not the least, the findings suggest that spammers do not depend on the feedback links from normal users to become more powerful, the unilateral links can make the hybrid attack effective enough. Since unilateral links are much cheaper, the hybrid attack will be a great threat to model-based social recommender systems.

  12. Mobile Application Recommender System

    OpenAIRE

    Davidsson, Christoffer

    2010-01-01

    With the amount of mobile applications available increasing rapidly, users have to put a lot of effort into finding applications of interest. The purpose of this thesis is to investigate how to aid users in the process of discovering new mobile applications by providing them with recommendations. A prototype system is then built as a proof-of-concept. The work of the thesis is divided into three phases where the aim of the first phase is to study related work and related systems to identify p...

  13. Implicit Motives and Men's Perceived Constraint in Fatherhood.

    Science.gov (United States)

    Ruppen, Jessica; Waldvogel, Patricia; Ehlert, Ulrike

    2016-01-01

    Research shows that implicit motives influence social relationships. However, little is known about their role in fatherhood and, particularly, how men experience their paternal role. Therefore, this study examined the association of implicit motives and fathers' perceived constraint due to fatherhood. Furthermore, we explored their relation to fathers' life satisfaction. Participants were fathers with biological children ( N = 276). They were asked to write picture stories, which were then coded for implicit affiliation and power motives. Perceived constraint and life satisfaction were assessed on a visual analog scale. A higher implicit need for affiliation was significantly associated with lower perceived constraint, whereas the implicit need for power had the opposite effect. Perceived constraint had a negative influence on life satisfaction. Structural equation modeling revealed significant indirect effects of implicit affiliation and power motives on life satisfaction mediated by perceived constraint. Our findings indicate that men with a higher implicit need for affiliation experience less constraint due to fatherhood, resulting in higher life satisfaction. The implicit need for power, however, results in more perceived constraint and is related to decreased life satisfaction.

  14. An implicit boundary integral method for computing electric potential of macromolecules in solvent

    Science.gov (United States)

    Zhong, Yimin; Ren, Kui; Tsai, Richard

    2018-04-01

    A numerical method using implicit surface representations is proposed to solve the linearized Poisson-Boltzmann equation that arises in mathematical models for the electrostatics of molecules in solvent. The proposed method uses an implicit boundary integral formulation to derive a linear system defined on Cartesian nodes in a narrowband surrounding the closed surface that separates the molecule and the solvent. The needed implicit surface is constructed from the given atomic description of the molecules, by a sequence of standard level set algorithms. A fast multipole method is applied to accelerate the solution of the linear system. A few numerical studies involving some standard test cases are presented and compared to other existing results.

  15. Family Shopping Recommendation System Using User Profile and Behavior Data

    OpenAIRE

    Jiacheng, Xu

    2017-01-01

    With the arrival of the big data era, recommendation system has been a hot technology for enterprises to streamline their sales. Recommendation algorithms for individual users have been extensively studied over the past decade. Most existing recommendation systems also focus on individual user recommendations, however in many daily activities, items are recommended to the groups not one person. As an effective means to solve the problem of group recommendation problem,we extend the single use...

  16. Multigrid Methods for Fully Implicit Oil Reservoir Simulation

    Science.gov (United States)

    Molenaar, J.

    1996-01-01

    In this paper we consider the simultaneous flow of oil and water in reservoir rock. This displacement process is modeled by two basic equations: the material balance or continuity equations and the equation of motion (Darcy's law). For the numerical solution of this system of nonlinear partial differential equations there are two approaches: the fully implicit or simultaneous solution method and the sequential solution method. In the sequential solution method the system of partial differential equations is manipulated to give an elliptic pressure equation and a hyperbolic (or parabolic) saturation equation. In the IMPES approach the pressure equation is first solved, using values for the saturation from the previous time level. Next the saturations are updated by some explicit time stepping method; this implies that the method is only conditionally stable. For the numerical solution of the linear, elliptic pressure equation multigrid methods have become an accepted technique. On the other hand, the fully implicit method is unconditionally stable, but it has the disadvantage that in every time step a large system of nonlinear algebraic equations has to be solved. The most time-consuming part of any fully implicit reservoir simulator is the solution of this large system of equations. Usually this is done by Newton's method. The resulting systems of linear equations are then either solved by a direct method or by some conjugate gradient type method. In this paper we consider the possibility of applying multigrid methods for the iterative solution of the systems of nonlinear equations. There are two ways of using multigrid for this job: either we use a nonlinear multigrid method or we use a linear multigrid method to deal with the linear systems that arise in Newton's method. So far only a few authors have reported on the use of multigrid methods for fully implicit simulations. Two-level FAS algorithm is presented for the black-oil equations, and linear multigrid for

  17. Goal-based structuring in a recommender systems

    NARCIS (Netherlands)

    Magoulas, G.D.; van Setten, Mark; Veenstra, Mettina; Chen, S.Y; Nijholt, Antinus; van Dijk, Elisabeth M.A.G.

    Recommender systems help people to find information that is interesting to them. However, current recommendation techniques only address the user's short-term and long-term interests, not their immediate interests. This paper describes a method to structure information (with or without using

  18. Earth Observing System, Conclusions and Recommendations

    Science.gov (United States)

    1984-01-01

    The following Earth Observing Systems (E.O.S.) recommendations were suggested: (1) a program must be initiated to ensure that present time series of Earth science data are maintained and continued. (2) A data system that provides easy, integrated, and complete access to past, present, and future data must be developed as soon as possible. (3) A long term research effort must be sustained to study and understand these time series of Earth observations. (4) The E.O.S. should be established as an information system to carry out those aspects of the above recommendations which go beyond existing and currently planned activities. (5) The scientific direction of the E.O.S. should be established and continued through an international scientific steering committee.

  19. Recommendations on future development of decision support systems

    DEFF Research Database (Denmark)

    MCarthur, Stephen; Chen, Minjiang; Marinelli, Mattia

    Deliverable 8.3 reports on the consolidation of experiences from visualisation, decision support prototypes experiments and recommendations on future developments of decision support systems......Deliverable 8.3 reports on the consolidation of experiences from visualisation, decision support prototypes experiments and recommendations on future developments of decision support systems...

  20. Implicit and explicit processes in social cognition

    DEFF Research Database (Denmark)

    Frith, Christopher; Frith, Uta

    2008-01-01

    In this review we consider research on social cognition in which implicit processes can be compared and contrasted with explicit, conscious processes. In each case, their function is distinct, sometimes complementary and sometimes oppositional. We argue that implicit processes in social interaction...... are automatic and are often opposed to conscious strategies. While we are aware of explicit processes in social interaction, we cannot always use them to override implicit processes. Many studies show that implicit processes facilitate the sharing of knowledge, feelings, and actions, and hence, perhaps...

  1. Implicit and explicit attitudes among students

    OpenAIRE

    Félix Neto

    2009-01-01

    Mental processing and mental experience is not the same thing. The former is the operation of the mind; the latter is the subjective life that emerges from these operations. In social evaluation, implicit and explicit attitudes express this distinction. https://implicit.harvard.edu/ was created to provide experience with the Implicit Association Test (IAT) a procedure designed to measure social knowledge that may operate outside of awareness. In this paper we examined the relationships betwee...

  2. A radiating shock evaluated using Implicit Monte Carlo Diffusion

    International Nuclear Information System (INIS)

    Cleveland, M.; Gentile, N.

    2013-01-01

    Implicit Monte Carlo [1] (IMC) has been shown to be very expensive when used to evaluate a radiation field in opaque media. Implicit Monte Carlo Diffusion (IMD) [2], which evaluates a spatial discretized diffusion equation using a Monte Carlo algorithm, can be used to reduce the cost of evaluating the radiation field in opaque media [2]. This work couples IMD to the hydrodynamics equations to evaluate opaque diffusive radiating shocks. The Lowrie semi-analytic diffusive radiating shock benchmark[a] is used to verify our implementation of the coupled system of equations. (authors)

  3. Requirements for Semantic Educational Recommender Systems in Formal E-Learning Scenarios

    Directory of Open Access Journals (Sweden)

    Jesus G. Boticario

    2011-07-01

    Full Text Available This paper analyzes how recommender systems can be applied to current e-learning systems to guide learners in personalized inclusive e-learning scenarios. Recommendations can be used to overcome current limitations of learning management systems in providing personalization and accessibility features. Recommenders can take advantage of standards-based solutions to provide inclusive support. To this end we have identified the need for developing semantic educational recommender systems, which are able to extend existing learning management systems with adaptive navigation support. In this paper we present three requirements to be considered in developing these semantic educational recommender systems, which are in line with the service-oriented approach of the third generation of learning management systems, namely: (i a recommendation model; (ii an open standards-based service-oriented architecture; and (iii a usable and accessible graphical user interface to deliver the recommendations.

  4. Free Energy, Enthalpy and Entropy from Implicit Solvent End-Point Simulations.

    Science.gov (United States)

    Fogolari, Federico; Corazza, Alessandra; Esposito, Gennaro

    2018-01-01

    Free energy is the key quantity to describe the thermodynamics of biological systems. In this perspective we consider the calculation of free energy, enthalpy and entropy from end-point molecular dynamics simulations. Since the enthalpy may be calculated as the ensemble average over equilibrated simulation snapshots the difficulties related to free energy calculation are ultimately related to the calculation of the entropy of the system and in particular of the solvent entropy. In the last two decades implicit solvent models have been used to circumvent the problem and to take into account solvent entropy implicitly in the solvation terms. More recently outstanding advancement in both implicit solvent models and in entropy calculations are making the goal of free energy estimation from end-point simulations more feasible than ever before. We review briefly the basic theory and discuss the advancements in light of practical applications.

  5. Free Energy, Enthalpy and Entropy from Implicit Solvent End-Point Simulations

    Directory of Open Access Journals (Sweden)

    Federico Fogolari

    2018-02-01

    Full Text Available Free energy is the key quantity to describe the thermodynamics of biological systems. In this perspective we consider the calculation of free energy, enthalpy and entropy from end-point molecular dynamics simulations. Since the enthalpy may be calculated as the ensemble average over equilibrated simulation snapshots the difficulties related to free energy calculation are ultimately related to the calculation of the entropy of the system and in particular of the solvent entropy. In the last two decades implicit solvent models have been used to circumvent the problem and to take into account solvent entropy implicitly in the solvation terms. More recently outstanding advancement in both implicit solvent models and in entropy calculations are making the goal of free energy estimation from end-point simulations more feasible than ever before. We review briefly the basic theory and discuss the advancements in light of practical applications.

  6. Evaluating Recommender Systems for Technology Enhanced Learning: A Quantitative Survey

    Science.gov (United States)

    Erdt, Mojisola; Fernandez, Alejandro; Rensing, Christoph

    2015-01-01

    The increasing number of publications on recommender systems for Technology Enhanced Learning (TEL) evidence a growing interest in their development and deployment. In order to support learning, recommender systems for TEL need to consider specific requirements, which differ from the requirements for recommender systems in other domains like…

  7. Changes of explicitly and implicitly measured self-esteem in the treatment of major depression: evidence for implicit self-esteem compensation.

    Science.gov (United States)

    Wegener, Ingo; Geiser, Franziska; Alfter, Susanne; Mierke, Jan; Imbierowicz, Katrin; Kleiman, Alexandra; Koch, Anne Sarah; Conrad, Rupert

    2015-04-01

    Self-esteem has been claimed to be an important factor in the development and maintenance of depression. Whereas explicit self-esteem is usually reduced in depressed individuals, studies on implicitly measured self-esteem in depression exhibit a more heterogeneous pattern of results, and the role of implicit self-esteem in depression is still ambiguous. Previous research on implicit self-esteem compensation (ISEC) revealed that implicit self-esteem can mirror processes of self-esteem compensation under conditions that threaten self-esteem. We assume that depressed individuals experience a permanent threat to their selves resulting in enduring processes of ISEC. We hypothesize that ISEC as measured by implicit self-esteem will decrease when individuals recover from depression. 45 patients with major depression received an integrative in-patient treatment in the Psychosomatic University Hospital Bonn, Germany. Depression was measured by the depression score of the Hospital Anxiety and Depression Scale (HADS-D). Self-esteem was assessed explicitly using the Rosenberg Self-Esteem Scale (RSES) and implicitly by the Implicit Association Test (IAT) and the Name Letter Test (NLT). As expected for a successful treatment of depression, depression scores declined during the eight weeks of treatment and explicit self-esteem rose. In line with our hypothesis, both measures of implicit self-esteem decreased, indicating reduced processes of ISEC. It still remains unclear, under which conditions there is an overlap of measures of implicit and explicit self-esteem. The results lend support to the concept of ISEC and demonstrate the relevance of implicit self-esteem and self-esteem compensation for the understanding of depression. Copyright © 2014 Elsevier Inc. All rights reserved.

  8. Social network supported process recommender system.

    Science.gov (United States)

    Ye, Yanming; Yin, Jianwei; Xu, Yueshen

    2014-01-01

    Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

  9. Social Network Supported Process Recommender System

    Directory of Open Access Journals (Sweden)

    Yanming Ye

    2014-01-01

    Full Text Available Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

  10. Building Personalized and Non Personalized Recommendation Systems

    OpenAIRE

    SNEHA KHATWANI; DR. M.B. CHANDAK

    2016-01-01

    The contents of e-Commerce such as music, movies, books and electronics goods are necessary for a modern life style. But, it becomes difficult to find content according to users likes and users preference. An approach which produces desirable results to solve such the problem is to develop "Recommender System." The Recommender System of an e-Commerce site selects and suggests the contents to meet user's preference automatically using data sets of previous users stored in database. There ca...

  11. Measuring Learner's Performance in E-Learning Recommender Systems

    Science.gov (United States)

    Ghauth, Khairil Imran; Abdullah, Nor Aniza

    2010-01-01

    A recommender system is a piece of software that helps users to identify the most interesting and relevant learning items from a large number of items. Recommender systems may be based on collaborative filtering (by user ratings), content-based filtering (by keywords), and hybrid filtering (by both collaborative and content-based filtering).…

  12. Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

    Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

  13. Semi-implicit and fully implicit shock-capturing methods for hyperbolic conservation laws with stiff source terms

    International Nuclear Information System (INIS)

    Yee, H.C.; Shinn, J.L.

    1986-12-01

    Some numerical aspects of finite-difference algorithms for nonlinear multidimensional hyperbolic conservation laws with stiff nonhomogenous (source) terms are discussed. If the stiffness is entirely dominated by the source term, a semi-implicit shock-capturing method is proposed provided that the Jacobian of the source terms possesses certain properties. The proposed semi-implicit method can be viewed as a variant of the Bussing and Murman point-implicit scheme with a more appropriate numerical dissipation for the computation of strong shock waves. However, if the stiffness is not solely dominated by the source terms, a fully implicit method would be a better choice. The situation is complicated by problems that are higher than one dimension, and the presence of stiff source terms further complicates the solution procedures for alternating direction implicit (ADI) methods. Several alternatives are discussed. The primary motivation for constructing these schemes was to address thermally and chemically nonequilibrium flows in the hypersonic regime. Due to the unique structure of the eigenvalues and eigenvectors for fluid flows of this type, the computation can be simplified, thus providing a more efficient solution procedure than one might have anticipated

  14. Semi-implicit and fully implicit shock-capturing methods for hyperbolic conservation laws with stiff source terms

    International Nuclear Information System (INIS)

    Yee, H.C.; Shinn, J.L.

    1987-01-01

    Some numerical aspects of finite-difference algorithms for nonlinear multidimensional hyperbolic conservation laws with stiff nonhomogeneous (source) terms are discussed. If the stiffness is entirely dominated by the source term, a semi-implicit shock-capturing method is proposed provided that the Jacobian of the source terms possesses certain properties. The proposed semi-implicit method can be viewed as a variant of the Bussing and Murman point-implicit scheme with a more appropriate numerical dissipation for the computation of strong shock waves. However, if the stiffness is not solely dominated by the source terms, a fully implicit method would be a better choice. The situation is complicated by problems that are higher than one dimension, and the presence of stiff source terms further complicates the solution procedures for alternating direction implicit (ADI) methods. Several alternatives are discussed. The primary motivation for constructing these schemes was to address thermally and chemically nonequilibrium flows in the hypersonic regime. Due to the unique structure of the eigenvalues and eigenvectors for fluid flows of this type, the computation can be simplified, thus providing a more efficient solution procedure than one might have anticipated. 46 references

  15. A Recommendation System to Facilitate Business Process Modeling.

    Science.gov (United States)

    Deng, Shuiguang; Wang, Dongjing; Li, Ying; Cao, Bin; Yin, Jianwei; Wu, Zhaohui; Zhou, Mengchu

    2017-06-01

    This paper presents a system that utilizes process recommendation technology to help design new business processes from scratch in an efficient and accurate way. The proposed system consists of two phases: 1) offline mining and 2) online recommendation. At the first phase, it mines relations among activity nodes from existing processes in repository, and then stores the extracted relations as patterns in a database. At the second phase, it compares the new process under construction with the premined patterns, and recommends proper activity nodes of the most matching patterns to help build a new process. Specifically, there are three different online recommendation strategies in this system. Experiments on both real and synthetic datasets are conducted to compare the proposed approaches with the other state-of-the-art ones, and the results show that the proposed approaches outperform them in terms of accuracy and efficiency.

  16. Characterizing implicit mental health associations across clinical domains.

    Science.gov (United States)

    Werntz, Alexandra J; Steinman, Shari A; Glenn, Jeffrey J; Nock, Matthew K; Teachman, Bethany A

    2016-09-01

    Implicit associations are relatively uncontrollable associations between concepts in memory. The current investigation focuses on implicit associations in four mental health domains (alcohol use, anxiety, depression, and eating disorders) and how these implicit associations: a) relate to explicit associations and b) self-reported clinical symptoms within the same domains, and c) vary based on demographic characteristics (age, gender, race, ethnicity, and education). Participants (volunteers over age 18 to a research website) completed implicit association (Implicit Association Tests), explicit association (self + psychopathology or attitudes toward food, using semantic differential items), and symptom measures at the Project Implicit Mental Health website tied to: alcohol use (N = 12,387), anxiety (N = 21,304), depression (N = 24,126), or eating disorders (N = 10,115). Within each domain, implicit associations showed small to moderate associations with explicit associations and symptoms, and predicted self-reported symptoms beyond explicit associations. In general, implicit association strength varied little by race and ethnicity, but showed small ties to age, gender, and education. This research was conducted on a public research and education website, where participants could take more than one of the studies. Among a large and diverse sample, implicit associations in the four domains are congruent with explicit associations and self-reported symptoms, and also add to our prediction of self-reported symptoms over and above explicit associations, pointing to the potential future clinical utility and validity of using implicit association measures with diverse populations. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Distributed Online Learning in Social Recommender Systems

    Science.gov (United States)

    Tekin, Cem; Zhang, Simpson; van der Schaar, Mihaela

    2014-08-01

    In this paper, we consider decentralized sequential decision making in distributed online recommender systems, where items are recommended to users based on their search query as well as their specific background including history of bought items, gender and age, all of which comprise the context information of the user. In contrast to centralized recommender systems, in which there is a single centralized seller who has access to the complete inventory of items as well as the complete record of sales and user information, in decentralized recommender systems each seller/learner only has access to the inventory of items and user information for its own products and not the products and user information of other sellers, but can get commission if it sells an item of another seller. Therefore the sellers must distributedly find out for an incoming user which items to recommend (from the set of own items or items of another seller), in order to maximize the revenue from own sales and commissions. We formulate this problem as a cooperative contextual bandit problem, analytically bound the performance of the sellers compared to the best recommendation strategy given the complete realization of user arrivals and the inventory of items, as well as the context-dependent purchase probabilities of each item, and verify our results via numerical examples on a distributed data set adapted based on Amazon data. We evaluate the dependence of the performance of a seller on the inventory of items the seller has, the number of connections it has with the other sellers, and the commissions which the seller gets by selling items of other sellers to its users.

  18. A collaborative approach for research paper recommender system.

    Science.gov (United States)

    Haruna, Khalid; Akmar Ismail, Maizatul; Damiasih, Damiasih; Sutopo, Joko; Herawan, Tutut

    2017-01-01

    Research paper recommenders emerged over the last decade to ease finding publications relating to researchers' area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collaborative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommendations. The novelty of our proposed approach is that it provides personalized recommendations regardless of the research field and regardless of the user's expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list.

  19. Hybrid Recommendation System Memanfaatkan Penggalian Frequent Itemset dan Perbandingan Keyword

    OpenAIRE

    Suka Parwita, Wayan Gede; Winarko, Edi

    2015-01-01

    Abstrak Recommendation system sering dibangun dengan memanfaatkan data peringkat item dan data identitas pengguna. Data peringkat item merupakan data yang langka pada sistem yang baru dibangun. Sedangkan, pemberian data identitas pada recommendation system dapat menimbulkan kekhawatiran penyalahgunaan data identitas. Hybrid recommendation system memanfaatkan algoritma penggalian frequent itemset dan perbandingan keyword dapat memberikan daftar rekomendasi tanpa menggunakan data identi...

  20. On the inexplicability of the implicit: differences in the information provided by implicit and explicit tests

    NARCIS (Netherlands)

    DeCoster, J.; Banner, M.J.; Smith, E.R.; Semin, G.R.

    2006-01-01

    Implicit measures are often preferred to overt questioning in many areas of psychology. Their covert nature allows them to circumvent conscious expectations and biases, theoretically providing more objective indicators of people's true attitudes and bel iefs. However, we argue that implicit and

  1. Simulation of coupled flow and mechanical deformation using IMplicit Pressure-Displacement Explicit Saturation (IMPDES) scheme

    KAUST Repository

    El-Amin, Mohamed

    2012-01-01

    The problem of coupled structural deformation with two-phase flow in porous media is solved numerically using cellcentered finite difference (CCFD) method. In order to solve the system of governed partial differential equations, the implicit pressure explicit saturation (IMPES) scheme that governs flow equations is combined with the the implicit displacement scheme. The combined scheme may be called IMplicit Pressure-Displacement Explicit Saturation (IMPDES). The pressure distribution for each cell along the entire domain is given by the implicit difference equation. Also, the deformation equations are discretized implicitly. Using the obtained pressure, velocity is evaluated explicitly, while, using the upwind scheme, the saturation is obtained explicitly. Moreover, the stability analysis of the present scheme has been introduced and the stability condition is determined.

  2. The Pivotal Role of Effort Beliefs in Mediating Implicit Theories of Intelligence and Achievement Goals and Academic Motivations

    Science.gov (United States)

    Tempelaar, Dirk T.; Rienties, Bart; Giesbers, Bas; Gijselaers, Wim H.

    2015-01-01

    Empirical studies into meaning systems surrounding implicit theories of intelligence typically entail two stringent assumptions: that different implicit theories and different effort beliefs represent opposite poles on a single scale, and that implicit theories directly impact the constructs as achievement goals and academic motivations. Through…

  3. Implicit perceptual-motor skill learning in mild cognitive impairment and Parkinson's disease.

    Science.gov (United States)

    Gobel, Eric W; Blomeke, Kelsey; Zadikoff, Cindy; Simuni, Tanya; Weintraub, Sandra; Reber, Paul J

    2013-05-01

    Implicit skill learning is hypothesized to depend on nondeclarative memory that operates independent of the medial temporal lobe (MTL) memory system and instead depends on cortico striatal circuits between the basal ganglia and cortical areas supporting motor function and planning. Research with the Serial Reaction Time (SRT) task suggests that patients with memory disorders due to MTL damage exhibit normal implicit sequence learning. However, reports of intact learning rely on observations of no group differences, leading to speculation as to whether implicit sequence learning is fully intact in these patients. Patients with Parkinson's disease (PD) often exhibit impaired sequence learning, but this impairment is not universally observed. Implicit perceptual-motor sequence learning was examined using the Serial Interception Sequence Learning (SISL) task in patients with amnestic Mild Cognitive Impairment (MCI; n = 11) and patients with PD (n = 15). Sequence learning in SISL is resistant to explicit learning and individually adapted task difficulty controls for baseline performance differences. Patients with MCI exhibited robust sequence learning, equivalent to healthy older adults (n = 20), supporting the hypothesis that the MTL does not contribute to learning in this task. In contrast, the majority of patients with PD exhibited no sequence-specific learning in spite of matched overall task performance. Two patients with PD exhibited performance indicative of an explicit compensatory strategy suggesting that impaired implicit learning may lead to greater reliance on explicit memory in some individuals. The differences in learning between patient groups provides strong evidence in favor of implicit sequence learning depending solely on intact basal ganglia function with no contribution from the MTL memory system.

  4. Understanding Cooperative Learning in Context-aware Recommender Systems

    DEFF Research Database (Denmark)

    Jiang, Na; Tan, Chee-Wee; Wang, Weiquan

    2017-01-01

    Context-Aware Recommender Systems (CARSs) are becoming commonplace. Yet, there is a paucity of studies that investigates how such systems could affect usage behavior from a user-system interaction perspective. Building on the Social Interdependence Theory (SIT), we construct a research model...... of users’ promotive interaction with CARSs, which in turn, dictates the performance of such recommender systems. Furthermore, we introduce scrutability features as design interventions that can be harnessed by developers to mitigate the impact of users’ promotive interaction on the performance of CARSs....

  5. An Ontology-Based Tourism Recommender System Based on Spreading Activation Model

    Science.gov (United States)

    Bahramian, Z.; Abbaspour, R. Ali

    2015-12-01

    A tourist has time and budget limitations; hence, he needs to select points of interest (POIs) optimally. Since the available information about POIs is overloading, it is difficult for a tourist to select the most appreciate ones considering preferences. In this paper, a new travel recommender system is proposed to overcome information overload problem. A recommender system (RS) evaluates the overwhelming number of POIs and provides personalized recommendations to users based on their preferences. A content-based recommendation system is proposed, which uses the information about the user's preferences and POIs and calculates a degree of similarity between them. It selects POIs, which have highest similarity with the user's preferences. The proposed content-based recommender system is enhanced using the ontological information about tourism domain to represent both the user profile and the recommendable POIs. The proposed ontology-based recommendation process is performed in three steps including: ontology-based content analyzer, ontology-based profile learner, and ontology-based filtering component. User's feedback adapts the user's preferences using Spreading Activation (SA) strategy. It shows the proposed recommender system is effective and improves the overall performance of the traditional content-based recommender systems.

  6. AN ONTOLOGY-BASED TOURISM RECOMMENDER SYSTEM BASED ON SPREADING ACTIVATION MODEL

    Directory of Open Access Journals (Sweden)

    Z. Bahramian

    2015-12-01

    Full Text Available A tourist has time and budget limitations; hence, he needs to select points of interest (POIs optimally. Since the available information about POIs is overloading, it is difficult for a tourist to select the most appreciate ones considering preferences. In this paper, a new travel recommender system is proposed to overcome information overload problem. A recommender system (RS evaluates the overwhelming number of POIs and provides personalized recommendations to users based on their preferences. A content-based recommendation system is proposed, which uses the information about the user’s preferences and POIs and calculates a degree of similarity between them. It selects POIs, which have highest similarity with the user’s preferences. The proposed content-based recommender system is enhanced using the ontological information about tourism domain to represent both the user profile and the recommendable POIs. The proposed ontology-based recommendation process is performed in three steps including: ontology-based content analyzer, ontology-based profile learner, and ontology-based filtering component. User’s feedback adapts the user’s preferences using Spreading Activation (SA strategy. It shows the proposed recommender system is effective and improves the overall performance of the traditional content-based recommender systems.

  7. Effects of high-frequency damping on iterative convergence of implicit viscous solver

    Science.gov (United States)

    Nishikawa, Hiroaki; Nakashima, Yoshitaka; Watanabe, Norihiko

    2017-11-01

    This paper discusses effects of high-frequency damping on iterative convergence of an implicit defect-correction solver for viscous problems. The study targets a finite-volume discretization with a one parameter family of damped viscous schemes. The parameter α controls high-frequency damping: zero damping with α = 0, and larger damping for larger α (> 0). Convergence rates are predicted for a model diffusion equation by a Fourier analysis over a practical range of α. It is shown that the convergence rate attains its minimum at α = 1 on regular quadrilateral grids, and deteriorates for larger values of α. A similar behavior is observed for regular triangular grids. In both quadrilateral and triangular grids, the solver is predicted to diverge for α smaller than approximately 0.5. Numerical results are shown for the diffusion equation and the Navier-Stokes equations on regular and irregular grids. The study suggests that α = 1 and 4/3 are suitable values for robust and efficient computations, and α = 4 / 3 is recommended for the diffusion equation, which achieves higher-order accuracy on regular quadrilateral grids. Finally, a Jacobian-Free Newton-Krylov solver with the implicit solver (a low-order Jacobian approximately inverted by a multi-color Gauss-Seidel relaxation scheme) used as a variable preconditioner is recommended for practical computations, which provides robust and efficient convergence for a wide range of α.

  8. Collaborative filtering recommendation model based on fuzzy clustering algorithm

    Science.gov (United States)

    Yang, Ye; Zhang, Yunhua

    2018-05-01

    As one of the most widely used algorithms in recommender systems, collaborative filtering algorithm faces two serious problems, which are the sparsity of data and poor recommendation effect in big data environment. In traditional clustering analysis, the object is strictly divided into several classes and the boundary of this division is very clear. However, for most objects in real life, there is no strict definition of their forms and attributes of their class. Concerning the problems above, this paper proposes to improve the traditional collaborative filtering model through the hybrid optimization of implicit semantic algorithm and fuzzy clustering algorithm, meanwhile, cooperating with collaborative filtering algorithm. In this paper, the fuzzy clustering algorithm is introduced to fuzzy clustering the information of project attribute, which makes the project belong to different project categories with different membership degrees, and increases the density of data, effectively reduces the sparsity of data, and solves the problem of low accuracy which is resulted from the inaccuracy of similarity calculation. Finally, this paper carries out empirical analysis on the MovieLens dataset, and compares it with the traditional user-based collaborative filtering algorithm. The proposed algorithm has greatly improved the recommendation accuracy.

  9. TrustRank: a Cold-Start tolerant recommender system

    Science.gov (United States)

    Zou, Haitao; Gong, Zhiguo; Zhang, Nan; Zhao, Wei; Guo, Jingzhi

    2015-02-01

    The explosive growth of the World Wide Web leads to the fast advancing development of e-commerce techniques. Recommender systems, which use personalised information filtering techniques to generate a set of items suitable to a given user, have received considerable attention. User- and item-based algorithms are two popular techniques for the design of recommender systems. These two algorithms are known to have Cold-Start problems, i.e., they are unable to effectively handle Cold-Start users who have an extremely limited number of purchase records. In this paper, we develop TrustRank, a novel recommender system which handles the Cold-Start problem by leveraging the user-trust networks which are commonly available for e-commerce applications. A user-trust network is formed by friendships or trust relationships that users specify among them. While it is straightforward to conjecture that a user-trust network is helpful for improving the accuracy of recommendations, a key challenge for using user-trust network to facilitate Cold-Start users is that these users also tend to have a very limited number of trust relationships. To address this challenge, we propose a pre-processing propagation of the Cold-Start users' trust network. In particular, by applying the personalised PageRank algorithm, we expand the friends of a given user to include others with similar purchase records to his/her original friends. To make this propagation algorithm scalable to a large amount of users, as required by real-world recommender systems, we devise an iterative computation algorithm of the original personalised TrustRank which can incrementally compute trust vectors for Cold-Start users. We conduct extensive experiments to demonstrate the consistently improvement provided by our proposed algorithm over the existing recommender algorithms on the accuracy of recommendations for Cold-Start users.

  10. Requirements for Semantic Educational Recommender Systems in Formal E-Learning Scenarios

    OpenAIRE

    Jesus G. Boticario; Olga C. Santos

    2011-01-01

    This paper analyzes how recommender systems can be applied to current e-learning systems to guide learners in personalized inclusive e-learning scenarios. Recommendations can be used to overcome current limitations of learning management systems in providing personalization and accessibility features. Recommenders can take advantage of standards-based solutions to provide inclusive support. To this end we have identified the need for developing semantic educational recommender systems, which ...

  11. Incorporating popularity in a personalized news recommender system

    Directory of Open Access Journals (Sweden)

    Nirmal Jonnalagedda

    2016-06-01

    Full Text Available Online news reading has become a widely popular way to read news articles from news sources around the globe. With the enormous amount of news articles available, users are easily overwhelmed by information of little interest to them. News recommender systems help users manage this flood by recommending articles based on user interests rather than presenting articles in order of their occurrence. We present our research on developing personalized news recommendation system with the help of a popular micro-blogging service, “Twitter.” News articles are ranked based on the popularity of the article identified from Twitter’s public timeline. In addition, users construct profiles based on their interests and news articles are also ranked based on their match to the user profile. By integrating these two approaches, we present a hybrid news recommendation model that recommends interesting news articles to the user based on their popularity as well as their relevance to the user profile.

  12. Personalised Information Gathering and Recommender Systems: Techniques and Trends

    Directory of Open Access Journals (Sweden)

    Xiaohui Tao

    2013-02-01

    Full Text Available With the explosive growth of resources available through the Internet, information mismatching and overload have become a severe concern to users.Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant and reliable information in a timely manner. Personalised information gathering and recommender systems represent state-of-the-art tools for efficient selection of the most relevant and reliable information resources, and the interest in such systems has increased dramatically over the last few years. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from a technological and social perspective. Aiming to promote high quality research in order to overcome these challenges, this paper provides a comprehensive survey on the recent work and achievements in the areas of personalised web information gathering and recommender systems. The report covers concept-based techniques exploited in personalised information gathering and recommender systems.

  13. Proactive Recommender Systems in Automotive Scenarios

    OpenAIRE

    Bader, Roland

    2013-01-01

    This thesis investigates proactive recommender systems to avoid information overload inside a car. The proposed system delivers context-adaptive items in the right situation. Explicit explanations are used to make the system comprehensible because it works without user request. To show the applicability of our system, we investigate the acceptance of the drivers. The results show that the drivers tend to accept such a system. Zur Vermeidung von Informationsüberflutung im Fahrzeug werden in...

  14. New Implicit General Linear Method | Ibrahim | Journal of the ...

    African Journals Online (AJOL)

    A New implicit general linear method is designed for the numerical olution of stiff differential Equations. The coefficients matrix is derived from the stability function. The method combines the single-implicitness or diagonal implicitness with property that the first two rows are implicit and third and fourth row are explicit.

  15. Integrating Information Extraction Agents into a Tourism Recommender System

    Science.gov (United States)

    Esparcia, Sergio; Sánchez-Anguix, Víctor; Argente, Estefanía; García-Fornes, Ana; Julián, Vicente

    Recommender systems face some problems. On the one hand information needs to be maintained updated, which can result in a costly task if it is not performed automatically. On the other hand, it may be interesting to include third party services in the recommendation since they improve its quality. In this paper, we present an add-on for the Social-Net Tourism Recommender System that uses information extraction and natural language processing techniques in order to automatically extract and classify information from the Web. Its goal is to maintain the system updated and obtain information about third party services that are not offered by service providers inside the system.

  16. Recommendation System of Program Based on REST Style

    Directory of Open Access Journals (Sweden)

    Song Jin Bao

    2016-01-01

    Full Text Available With the popularity of digital TV, TV programs have been on the increase no matter in both the number and species, which brought many choice to the users. Although the digital TV has increased largely in the selectivity, it has become a fussy process that users search for programs which they are interested in. So there is need to have an efficient program recommendation system to solve the problem that is “information overload” for users. It can not only help users to get the program which they require, but also bring convenience to people’s life. The program recommendation system named MyView is planned and designed, aimed to providing an efficient information platform. The system also involves intelligent recommendation. The information guide will trigger the recommendation engine after users registering information, the engine will accord to the data in the guide information to make the personalized program recommendation. The system was deployed in the Tomcat and Apache integration servers on my localhost, so it also belongs to the Web application based on J2EE platform. AJAX is used that can achieve a good user experience to develop web presentation layer on MyView PC browser with flexible interface performance. The background of business services uses the hierarchical form. MyView System uses the CXF framework and Hibernate to equip controller and data persistence layer in the Spring container. The overall framework of the system uses the REST style, in order to extend the performance and function later. Background service layer with uniform interface, marked by the URI resource. At the same time, HTTP requestion is submitted by the AJAX to obtain services provided by resources. Finally, we can analyze and summary the features of MyView System.

  17. E-Learning Recommender System Based on Collaborative Filtering and Ontology

    OpenAIRE

    John Tarus; Zhendong Niu; Bakhti Khadidja

    2017-01-01

    In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving ...

  18. Which recommender system can best fit social learning platforms?

    NARCIS (Netherlands)

    Fazeli, Soude; Loni, Babak; Drachsler, Hendrik; Sloep, Peter

    2014-01-01

    In this presentation, we present a study that aims to develop a recommender system for social learning platforms that combine traditional learning management systems with commercial social networks like Facebook. We therefore take into account social interactions of users to make recommendations on

  19. Which Recommender System Can Best Fit Social Learning Platforms?

    NARCIS (Netherlands)

    Fazeli, Soude; Loni, Babak; Drachsler, Hendrik; Sloep, Peter

    2014-01-01

    This study aims to develop a recommender system for social learning platforms that combine traditional learning management systems with commercial social networks like Facebook. We therefore take into account social interactions of users to make recommendations on learning resources. We propose to

  20. Towards a Legal Recommender System

    NARCIS (Netherlands)

    Winkels, R.; Boer, A.; Vredebregt, B.; van Someren, A.

    2014-01-01

    In this paper we present the results of ongoing research aimed at a legal recommender system where users of a legislative portal receive suggestions of other relevant sources of law, given a focus document. We describe how we make references in case law to legislation explicit and machine readable,

  1. Recommendation strategies for e-learning: preliminary effects of a personal recommender system for lifelong learners

    NARCIS (Netherlands)

    Drachsler, Hendrik; Hummel, Hans; Van den Berg, Bert; Eshuis, Jannes; Berlanga, Adriana; Nadolski, Rob; Waterink, Wim; Boers, Nanda; Koper, Rob

    2007-01-01

    Drachsler, H., Hummel, H. G. K., Van den Berg, B., Eshuis, J., Berlanga, A. J., Nadolski, R. J., Waterink, W., Boers, N., & Koper, R. (2007). Recommendation strategies for e-learning: preliminary effects of personal recommender system for lifelong learners. Unpublished manuscript.

  2. Defensive function of persecutory delusion and discrepancy between explicit and implicit self-esteem in schizophrenia: study using the Brief Implicit Association Test.

    Science.gov (United States)

    Nakamura, Mitsuo; Hayakawa, Tomomi; Okamura, Aiko; Kohigashi, Mutsumi; Fukui, Kenji; Narumoto, Jin

    2015-01-01

    If delusions serve as a defense mechanism in schizophrenia patients with paranoia, then they should show normal or high explicit self-esteem and low implicit self-esteem. However, the results of previous studies are inconsistent. One possible explanation for this inconsistency is that there are two types of paranoia, "bad me" (self-blaming) paranoia and "poor me" (non-self-blaming) paranoia. We thus examined implicit and explicit self-esteem and self-blaming tendency in patients with schizophrenia and schizoaffective disorder. We hypothesized that patients with paranoia would show lower implicit self-esteem and only those with non-self-blaming paranoia would experience a discrepancy between explicit and implicit self-esteem. Participants consisted of patients with schizophrenia and schizoaffective disorder recruited from a day hospital (N=71). Participants were assessed for psychotic symptoms, using the Brief Psychiatric Rating Scale (BPRS), and self-blaming tendency, using the brief COPE. We also assessed explicit self-esteem, using the Rosenberg Self-Esteem Scale (RSES), implicit self-esteem, using Brief Implicit Association Test (BIAT), and discrepancy between explicit and implicit self-esteem. Contrary to our hypothesis, implicit self-esteem in paranoia and nonparanoia showed no statistical difference. As expected, only patients with non-self-blaming paranoia experienced a discrepancy between explicit and implicit self-esteem; other groups showed no such discrepancy. These results suggest that persecutory delusion plays a defensive role in non-self-blaming paranoia.

  3. Implicit Motives and Men’s Perceived Constraint in Fatherhood

    Science.gov (United States)

    Ruppen, Jessica; Waldvogel, Patricia; Ehlert, Ulrike

    2016-01-01

    Research shows that implicit motives influence social relationships. However, little is known about their role in fatherhood and, particularly, how men experience their paternal role. Therefore, this study examined the association of implicit motives and fathers’ perceived constraint due to fatherhood. Furthermore, we explored their relation to fathers’ life satisfaction. Participants were fathers with biological children (N = 276). They were asked to write picture stories, which were then coded for implicit affiliation and power motives. Perceived constraint and life satisfaction were assessed on a visual analog scale. A higher implicit need for affiliation was significantly associated with lower perceived constraint, whereas the implicit need for power had the opposite effect. Perceived constraint had a negative influence on life satisfaction. Structural equation modeling revealed significant indirect effects of implicit affiliation and power motives on life satisfaction mediated by perceived constraint. Our findings indicate that men with a higher implicit need for affiliation experience less constraint due to fatherhood, resulting in higher life satisfaction. The implicit need for power, however, results in more perceived constraint and is related to decreased life satisfaction. PMID:27933023

  4. Implicit Motives and Men’s Perceived Constraint in Fatherhood

    Directory of Open Access Journals (Sweden)

    Jessica Ruppen

    2016-11-01

    Full Text Available Research shows that implicit motives influence social relationships. However, little is known about their role in fatherhood and, particularly, how men experience their paternal role. Therefore, this study examined the association of implicit motives and fathers’ perceived constraint due to fatherhood. Furthermore, we explored their relation to fathers’ life satisfaction. Participants were fathers with biological children (N = 276. They were asked to write picture stories, which were then coded for implicit affiliation and power motives. Perceived constraint and life satisfaction were assessed on a visual analog scale. A higher implicit need for affiliation was significantly associated with lower perceived constraint, whereas the implicit need for power had the opposite effect. Perceived constraint had a negative influence on life satisfaction. Structural equation modeling revealed significant indirect effects of implicit affiliation and power motives on life satisfaction mediated by perceived constraint. Our findings indicate that men with a higher implicit need for affiliation experience less constraint due to fatherhood, resulting in higher life satisfaction. The implicit need for power, however, results in more perceived constraint and is related to decreased life satisfaction.

  5. Collaborative User Network Embedding for Social Recommender Systems

    KAUST Repository

    Zhang, Chuxu; Yu, Lu; Wang, Yan; Shah, Chirag; Zhang, Xiangliang

    2017-01-01

    To address the issue of data sparsity and cold-start in recommender system, social information (e.g., user-user trust links) has been introduced to complement rating data for improving the performances of traditional model-based recommendation

  6. NUEN-618 Class Project: Actually Implicit Monte Carlo

    Energy Technology Data Exchange (ETDEWEB)

    Vega, R. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Brunner, T. A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-12-14

    This research describes a new method for the solution of the thermal radiative transfer (TRT) equations that is implicit in time which will be called Actually Implicit Monte Carlo (AIMC). This section aims to introduce the TRT equations, as well as the current workhorse method which is known as Implicit Monte Carlo (IMC). As the name of the method proposed here indicates, IMC is a misnomer in that it is only semi-implicit, which will be shown in this section as well.

  7. Algorithms for Academic Search and Recommendation Systems

    DEFF Research Database (Denmark)

    Amolochitis, Emmanouil

    2014-01-01

    are part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. In the third part of the work we present the design of a quantitative association rule mining algorithm. The introduced mining algorithm processes......In this work we present novel algorithms for academic search, recommendation and association rules mining. In the first part of the work we introduce a novel hierarchical heuristic scheme for re-ranking academic publications. The scheme is based on the hierarchical combination of a custom...... implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. On the second part we describe the design of hybrid recommender ensemble (user, item and content based). The newly introduced algorithms...

  8. A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

    Science.gov (United States)

    Staels, Eva; Van den Broeck, Wim

    2017-05-01

    Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  9. Role of implicit learning abilities in metaphor understanding.

    Science.gov (United States)

    Drouillet, Luc; Stefaniak, Nicolas; Declercq, Christelle; Obert, Alexandre

    2018-05-01

    Although the use of metaphors is a central component of language, the processes that sustain their comprehension have yet to be specified. Work in the fields of both metaphors and implicit learning suggests that implicit learning abilities facilitate the comprehension of metaphors. However, to date, no study has directly explored the relationships between the understanding of metaphors and so-called implicit learning tasks. We used a meaning decision task comparing literal, metaphorical and meaningless expressions to assess metaphor understanding and a probabilistic serial reaction time task for assessing implicit learning. Our results show that implicit learning positively predicts the time gap between responses to literal and metaphorical expressions and negatively predicts the difference between metaphorical and meaningless expressions. Thus, when confronted with novel metaphors, participants with higher implicit learning abilities are better able to identify that the expressions have some meaning. These results are interpreted in the context of metaphor understanding and psycholinguistic theories. Copyright © 2018 Elsevier Inc. All rights reserved.

  10. Diagonally Implicit Runge-Kutta Methods for Ordinary Differential Equations. A Review

    Science.gov (United States)

    Kennedy, Christopher A.; Carpenter, Mark H.

    2016-01-01

    A review of diagonally implicit Runge-Kutta (DIRK) methods applied to rst-order ordinary di erential equations (ODEs) is undertaken. The goal of this review is to summarize the characteristics, assess the potential, and then design several nearly optimal, general purpose, DIRK-type methods. Over 20 important aspects of DIRKtype methods are reviewed. A design study is then conducted on DIRK-type methods having from two to seven implicit stages. From this, 15 schemes are selected for general purpose application. Testing of the 15 chosen methods is done on three singular perturbation problems. Based on the review of method characteristics, these methods focus on having a stage order of two, sti accuracy, L-stability, high quality embedded and dense-output methods, small magnitudes of the algebraic stability matrix eigenvalues, small values of aii, and small or vanishing values of the internal stability function for large eigenvalues of the Jacobian. Among the 15 new methods, ESDIRK4(3)6L[2]SA is recommended as a good default method for solving sti problems at moderate error tolerances.

  11. Recommender systems for technology enhanced learning research trends and applications

    CERN Document Server

    Manouselis, Nikos; Verbert, Katrien

    2014-01-01

    Presents cutting edge research from leading experts in the growing field of Recommender Systems for Technology Enhanced Learning (RecSys TEL) International contributions are included to demonstrate the merging of various efforts and communities Topics include: Linked Data and the Social Web as Facilitators for TEL Recommender Systems in Research and Practice, Personalised Learning-Plan Recommendations in Game-Based Learning and Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem

  12. Healthcare information systems: data mining methods in the creation of a clinical recommender system

    Science.gov (United States)

    Duan, L.; Street, W. N.; Xu, E.

    2011-05-01

    Recommender systems have been extensively studied to present items, such as movies, music and books that are likely of interest to the user. Researchers have indicated that integrated medical information systems are becoming an essential part of the modern healthcare systems. Such systems have evolved to an integrated enterprise-wide system. In particular, such systems are considered as a type of enterprise information systems or ERP system addressing healthcare industry sector needs. As part of efforts, nursing care plan recommender systems can provide clinical decision support, nursing education, clinical quality control, and serve as a complement to existing practice guidelines. We propose to use correlations among nursing diagnoses, outcomes and interventions to create a recommender system for constructing nursing care plans. In the current study, we used nursing diagnosis data to develop the methodology. Our system utilises a prefix-tree structure common in itemset mining to construct a ranked list of suggested care plan items based on previously-entered items. Unlike common commercial systems, our system makes sequential recommendations based on user interaction, modifying a ranked list of suggested items at each step in care plan construction. We rank items based on traditional association-rule measures such as support and confidence, as well as a novel measure that anticipates which selections might improve the quality of future rankings. Since the multi-step nature of our recommendations presents problems for traditional evaluation measures, we also present a new evaluation method based on average ranking position and use it to test the effectiveness of different recommendation strategies.

  13. Shilling Attack Prevention for Recommender Systems Using Social-based Clustering

    KAUST Repository

    Lee, Tak

    2011-06-06

    A Recommender System (RS) is a system that utilizes user and item information to predict the feeling of users towards unfamiliar items. Recommender Systems have become popular tools for online stores due to their usefulness in confidently recommending items to users. A popular algorithm for recommender system is Collaborative Filtering (CF). CF uses other users\\' profiles to predict whether a user is interested in a particular object. This system, however, is vulnerable to malicious users seeking to promote items by manipulating rating predictions with fake user profiles. Profiles with behaviors similar to "victim" users alter the prediction of a Recommender System. Manipulating rating predictions through injected profiles is referred to as a shilling attack. It is important to develop shilling attack prevention frameworks for to protect the trustworthiness of Recommender Systems. In this thesis, we will demonstrate a new methodology that utilizes social information to prevent malicious users from manipulating the prediction system. The key element in our new methodology rests upon the concept of trust among real users, an element we claim absent among malicious profiles. In order to use trust information for shilling attack prevention, we first develop a weighting system which makes the system rely more on trustworthy users when making predictions. We then use this trust information to cluster out untrustworthy users to improve rating robustness. The robustness of the new and classic systems is then evaluated with data from a public commercial consumer RS, Epinions.com. Several complexity reduction procedures are also introduced to make implementing the algorithms mentioned possible for a huge commercial database.

  14. On implicit racial prejudice against infants

    NARCIS (Netherlands)

    Wolf, L.J.; Maio, G.R.; Karremans, J.C.T.M.; Leygue, C.

    2017-01-01

    Because of the innocence and dependence of children, it would be reassuring to believe that implicit racial prejudice against out-group children is lower than implicit prejudice against out-group adults. Yet, prior research has not directly tested whether or not adults exhibit less spontaneous

  15. FERTILIZER RECOMMENDATION SYSTEM FOR MELON BASED ON NUTRITIONAL BALANCE

    Directory of Open Access Journals (Sweden)

    José Aridiano Lima de Deus

    2015-04-01

    Full Text Available Melon is one of the most demanding cucurbits regarding fertilization, requiring knowledge of soils, crop nutritional requirements, time of application, and nutrient use efficiency for proper fertilization. Developing support systems for decision-making for fertilization that considers these variables in nutrient requirement and supply is necessary. The objective of this study was parameterization of a fertilizer recommendation system for melon (Ferticalc-melon based on nutritional balance. To estimate fertilizer recommendation, the system considers the requirement subsystem (REQ, which includes the demand for nutrients by the plant, and the supply subsystem (SUP, which corresponds to the supply of nutrients through the soil and irrigation water. After determining the REQtotal and SUPtotal, the system calculates the nutrient balances for N, P, K, Ca, Mg, and S, recommending fertilizer application if the balance is negative (SUP < REQ, but not if the balance is positive or zero (SUP ≥ REQ. Simulations were made for different melon types (Yellow, Cantaloupe, Galia and Piel-de-sapo, with expected yield of 45 t ha-1. The system estimated that Galia type was the least demanding in P, while Piel-de-sapo was the most demanding. Cantaloupe was the least demanding for N and Ca, while the Yellow type required less K, Mg, and S. As compared to other fertilizer recommendation methods adopted in Brazil, the Ferticalc system was more dynamic and flexible. Although the system has shown satisfactory results, it needs to be evaluated under field conditions to improve its recommendations.

  16. Evaluation of Explanation Interfaces in Recommender Systems

    Directory of Open Access Journals (Sweden)

    Sergio Cleger-Tamayo

    2017-05-01

    Full Text Available Explaining interfaces become a useful tool in systems that have a lot of content to evaluate by users. The different interfaces represent a help for the undecided users or those who consider systems as boxed black smart. These systems present recommendations to users based on different learning models. In this paper, we present the different objectives of the explanation interfaces and some of the criteria that you can evaluate, as well as a proposal of metrics to obtain results in the experiments. Finally, we showed the main results of a study with real users and their interaction with e-commerce systems. Among the main results, highlight the positive impact in relation to the time of interaction with the applications and acceptance of the recommendations received.

  17. Where to publish? Development of a recommender system for academic publishing

    OpenAIRE

    Gutknecht, Christian

    2014-01-01

    This thesis using the method of research design is about creating a journal recommendation system for authors. Existing systems like JANE or whichjournal.com offer recommendations based on similarities of the content. This study invests how more sophisticated factors like openness, price (subscription or article processing charge), speed of publication can be included in the ranking of a recommendation system. The recommendation should also consider the expectations from other stakeholders li...

  18. Massively Parallel and Scalable Implicit Time Integration Algorithms for Structural Dynamics

    Science.gov (United States)

    Farhat, Charbel

    1997-01-01

    Explicit codes are often used to simulate the nonlinear dynamics of large-scale structural systems, even for low frequency response, because the storage and CPU requirements entailed by the repeated factorizations traditionally found in implicit codes rapidly overwhelm the available computing resources. With the advent of parallel processing, this trend is accelerating because of the following additional facts: (a) explicit schemes are easier to parallelize than implicit ones, and (b) explicit schemes induce short range interprocessor communications that are relatively inexpensive, while the factorization methods used in most implicit schemes induce long range interprocessor communications that often ruin the sought-after speed-up. However, the time step restriction imposed by the Courant stability condition on all explicit schemes cannot yet be offset by the speed of the currently available parallel hardware. Therefore, it is essential to develop efficient alternatives to direct methods that are also amenable to massively parallel processing because implicit codes using unconditionally stable time-integration algorithms are computationally more efficient when simulating the low-frequency dynamics of aerospace structures.

  19. Electronic Resources Management System: Recommendation Report 2017

    KAUST Repository

    Ramli, Rindra M.

    2017-01-01

    This recommendation report provides an overview of the selection process for the new Electronic Resources Management System. The library has decided to move away from Innovative Interfaces Millennium ERM module. The library reviewed 3 system

  20. A Multi-context BDI Recommender System: from Theory to Simulation

    OpenAIRE

    Ben Othmane , Amel; Tettamanzi , Andrea G. B.; Villata , Serena; Le Thanh , Nhan

    2016-01-01

    International audience; In this paper, a simulation of a multi-agent recommender system is presented and developed in the NetLogo platform. The specification of this recommender system is based on the well known Belief-Desire-Intention agent architecture applied to multi-context systems, extended with contexts foradditional reasoning abilities, especially social ones. The main goal of this simulation study is, besides illustrating the usefulness and feasibility of our agent-based recommender ...

  1. A generic semi-implicit coupling methodology for use in RELAP5-3Dcopyright

    International Nuclear Information System (INIS)

    Aumiller, D.L.; Tomlinson, E.T.; Weaver, W.L.

    2000-01-01

    A generic semi-implicit coupling methodology has been developed and implemented in the RELAP5-3Dcopyright computer program. This methodology allows RELAP5-3Dcopyright to be used with other computer programs to perform integrated analyses of nuclear power reactor systems and related experimental facilities. The coupling methodology potentially allows different programs to be used to model different portions of the system. The programs are chosen based on their capability to model the phenomena that are important in the simulation in the various portions of the system being considered. The methodology was demonstrated using a test case in which the test geometry was divided into two parts each of which was solved as a RELAP5-3Dcopyright simulation. This test problem exercised all of the semi-implicit coupling features which were installed in RELAP5-3D0. The results of this verification test case show that the semi-implicit coupling methodology produces the same answer as the simulation of the test system as a single process

  2. Defensive function of persecutory delusion and discrepancy between explicit and implicit self-esteem in schizophrenia: study using the Brief Implicit Association Test

    Science.gov (United States)

    Nakamura, Mitsuo; Hayakawa, Tomomi; Okamura, Aiko; Kohigashi, Mutsumi; Fukui, Kenji; Narumoto, Jin

    2015-01-01

    Background If delusions serve as a defense mechanism in schizophrenia patients with paranoia, then they should show normal or high explicit self-esteem and low implicit self-esteem. However, the results of previous studies are inconsistent. One possible explanation for this inconsistency is that there are two types of paranoia, “bad me” (self-blaming) paranoia and “poor me” (non-self-blaming) paranoia. We thus examined implicit and explicit self-esteem and self-blaming tendency in patients with schizophrenia and schizoaffective disorder. We hypothesized that patients with paranoia would show lower implicit self-esteem and only those with non-self-blaming paranoia would experience a discrepancy between explicit and implicit self-esteem. Methods Participants consisted of patients with schizophrenia and schizoaffective disorder recruited from a day hospital (N=71). Participants were assessed for psychotic symptoms, using the Brief Psychiatric Rating Scale (BPRS), and self-blaming tendency, using the brief COPE. We also assessed explicit self-esteem, using the Rosenberg Self-Esteem Scale (RSES), implicit self-esteem, using Brief Implicit Association Test (BIAT), and discrepancy between explicit and implicit self-esteem. Results Contrary to our hypothesis, implicit self-esteem in paranoia and nonparanoia showed no statistical difference. As expected, only patients with non-self-blaming paranoia experienced a discrepancy between explicit and implicit self-esteem; other groups showed no such discrepancy. Conclusion These results suggest that persecutory delusion plays a defensive role in non-self-blaming paranoia. PMID:25565849

  3. PERSON-Personalized Expert Recommendation System for Optimized Nutrition.

    Science.gov (United States)

    Chen, Chih-Han; Karvela, Maria; Sohbati, Mohammadreza; Shinawatra, Thaksin; Toumazou, Christofer

    2018-02-01

    The rise of personalized diets is due to the emergence of nutrigenetics and genetic tests services. However, the recommendation system is far from mature to provide personalized food suggestion to consumers for daily usage. The main barrier of connecting genetic information to personalized diets is the complexity of data and the scalability of the applied systems. Aiming to cross such barriers and provide direct applications, a personalized expert recommendation system for optimized nutrition is introduced in this paper, which performs direct to consumer personalized grocery product filtering and recommendation. Deep learning neural network model is applied to achieve automatic product categorization. The ability of scaling with unknown new data is achieved through the generalized representation of word embedding. Furthermore, the categorized products are filtered with a model based on individual genetic data with associated phenotypic information and a case study with databases from three different sources is carried out to confirm the system.

  4. Cooperative Epistemic Multi-Agent Planning With Implicit Coordination

    DEFF Research Database (Denmark)

    Engesser, Thorsten; Bolander, Thomas; Mattmüller, Robert

    2015-01-01

    , meaning coordination is only allowed implicitly by means of the available epistemic actions. While this approach can be fruitfully applied to model reasoning in some simple social situations, we also provide some benchmark applications to show that the concept is useful for multi-agent systems in practice....

  5. On the velocity space discretization for the Vlasov-Poisson system: comparison between implicit Hermite spectral and Particle-in-Cell methods

    NARCIS (Netherlands)

    E. Camporeale (Enrico); G.L. Delzanno; B.K. Bergen; J.D. Moulton

    2016-01-01

    htmlabstractWe describe a spectral method for the numerical solution of the Vlasov–Poisson system where the velocity space is decomposed by means of an Hermite basis, and the configuration space is discretized via a Fourier decomposition. The novelty of our approach is an implicit time

  6. Finger Search in the Implicit Model

    DEFF Research Database (Denmark)

    Brodal, Gerth Stølting; Nielsen, Jesper Asbjørn Sindahl; Truelsen, Jakob

    2012-01-01

    We address the problem of creating a dictionary with the finger search property in the strict implicit model, where no information is stored between operations, except the array of elements. We show that for any implicit dictionary supporting finger searches in q(t) = Ω(logt) time, the time to move...... the finger to another element is Ω(q− 1(logn)), where t is the rank distance between the query element and the finger. We present an optimal implicit static structure matching this lower bound. We furthermore present a near optimal implicit dynamic structure supporting search, change-finger, insert......, and delete in times $\\mathcal{O}(q(t))$, $\\mathcal{O}(q^{-1}(\\log n)\\log n)$, $\\mathcal{O}(\\log n)$, and $\\mathcal{O}(\\log n)$, respectively, for any q(t) = Ω(logt). Finally we show that the search operation must take Ω(logn) time for the special case where the finger is always changed to the element...

  7. Implicit environmental costs in hydroelectric development

    International Nuclear Information System (INIS)

    Carlsen, A.J.; Wenstoep, F.; Strand, J.

    1992-01-01

    The ranking of hydropower projects under the Norwegian Master Plan for Water Resources is used to derive implicit government preferences for a number of environmental attributes described by ordinal scores for each project. Higher negative scores are generally associated with greater implicit willingness to pay to avoid the environmental damage tied to the attribute, caused by hydropower development. The total (ordinary economic and implicit environmental) cost for each project are derived, and the environmental costs per capacity unit are found to be on the same order as the economic costs, lower for projects ranked for early exploitation, and higher for projects to be saved permanently. An implicit long-run marginal cost curve for Norwegian hydropower development is derived, which is generally upward sloping, but not uniformly so. This can be due to the model specification problems or ranking inconsistencies, both of which are likely to be present. 11 refs., 7 figs., 1 tab

  8. Do health care providers' attitudes towards back pain predict their treatment recommendations? Differential predictive validity of implicit and explicit attitude measures

    NARCIS (Netherlands)

    Houben, R.M.A.; Gijsen, A.; Peterson, J.; de Jong, P.J.; Vlaeyen, J.W.S.

    The current study aimed to measure the differential predictive value of implicit and explicit attitude measures on treatment behaviour of health care providers. Thirty-six physiotherapy students completed a measure of explicit treatment attitude (Pain Attitudes And Beliefs Scale For

  9. Ambulatory assessed implicit affect is associated with salivary cortisol

    Directory of Open Access Journals (Sweden)

    Joram eMossink

    2015-02-01

    Full Text Available One of the presumed pathways linking negative emotions to adverse somatic health is an overactive HPA-axis, usually indicated by elevated cortisol levels. Traditionally, research has focused on consciously reported negative emotions. Yet, given that the majority of information processing occurs without conscious awareness, stress physiology might also be influenced by affective processes that people are not aware of. In a 24-hour ambulatory study we examined whether cortisol levels were associated with two implicit measures. Implicit affect was assessed using the Implicit Positive and Negative Affect Test, and implicit negative memory bias was assessed with the word fragment completion tasks. In 55 healthy participants, we measured subjective stress levels, worries, implicit and explicit affect each hour during waking hours. Also, saliva samples were collected at three fixed times during the day, as well as upon waking and 30 minutes thereafter (cortisol awakening response. Multilevel analyses of the daytime cortisol levels revealed that the presence of an implicit negative memory bias was associated with increased cortisol levels. Additionally, implicit PA and, unexpectedly, implicit NA were negatively associated with cortisol levels. Finally, participants demonstrating higher levels of implicit sadness during the first measurement day, had a stronger cortisol rise upon awakening at the next day. Contrary to previous research, no associations between explicit affect and cortisol were apparent. The current study was the first to examine the concurrent relation between implicit measures and stress physiology in daily life. The results suggest that the traditional focus on consciously reported feelings and emotions is limited, and that implicit measures can add to our understanding of how stress and emotions contribute to daily physiological activity and, in the long term, health problems.

  10. Improvement of recommender systems considering big data of users ...

    African Journals Online (AJOL)

    Regarding to the increase in the online social networks services during the recent years, the recommender system has turned into an emerging research subject. Currently, regarding to the fast and consistent expansion of using the internet, the necessity of a recommender system for refining the large volume of data has ...

  11. Mothers' intentions to support children's physical activity related to attention and implicit agreement with advertisements.

    Science.gov (United States)

    Berry, Tanya R; Craig, Cora L; Faulkner, Guy; Latimer, Amy; Rhodes, Ryan; Spence, John C; Tremblay, Mark S

    2014-02-01

    ParticipACTION's Think Again campaign targeted mothers who think their children are sufficiently active, yet whose children do not achieve recommended amounts of physical activity. This research examined the relationship of mothers' intentions to support children's physical activity with explicit believability and implicit agreement with the Think Again campaign message, attention paid to the advertisement, involvement with the issue, concern regarding children's inactivity, and attitudes. Participants were mothers from Edmonton, Canada (N = 102) who viewed one Think Again advertisement then completed a measure of implicit agreement with the campaign message and questionnaires. The mothers who paid attention to the message and were concerned for their own children were more likely to intend to act on campaign messages. The majority of participants implicitly agreed that children's physical inactivity was a problem, but there was less agreement that physical inactivity was a problem for their own children. Participants automatically tended to agree with campaign messages when the focus was on children in general, but there was greater disagreement when asked about participant's own children. Why most mothers were not in agreement with the reality of how much physical activity their children needs remains to be determined.

  12. Implicit assumptions underlying simple harvest models of marine bird populations can mislead environmental management decisions.

    Science.gov (United States)

    O'Brien, Susan H; Cook, Aonghais S C P; Robinson, Robert A

    2017-10-01

    Assessing the potential impact of additional mortality from anthropogenic causes on animal populations requires detailed demographic information. However, these data are frequently lacking, making simple algorithms, which require little data, appealing. Because of their simplicity, these algorithms often rely on implicit assumptions, some of which may be quite restrictive. Potential Biological Removal (PBR) is a simple harvest model that estimates the number of additional mortalities that a population can theoretically sustain without causing population extinction. However, PBR relies on a number of implicit assumptions, particularly around density dependence and population trajectory that limit its applicability in many situations. Among several uses, it has been widely employed in Europe in Environmental Impact Assessments (EIA), to examine the acceptability of potential effects of offshore wind farms on marine bird populations. As a case study, we use PBR to estimate the number of additional mortalities that a population with characteristics typical of a seabird population can theoretically sustain. We incorporated this level of additional mortality within Leslie matrix models to test assumptions within the PBR algorithm about density dependence and current population trajectory. Our analyses suggest that the PBR algorithm identifies levels of mortality which cause population declines for most population trajectories and forms of population regulation. Consequently, we recommend that practitioners do not use PBR in an EIA context for offshore wind energy developments. Rather than using simple algorithms that rely on potentially invalid implicit assumptions, we recommend use of Leslie matrix models for assessing the impact of additional mortality on a population, enabling the user to explicitly define assumptions and test their importance. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. I should not recommend it to you even if you will like it: the ethics of recommender systems

    Science.gov (United States)

    Tang, Tiffany Ya; Winoto, Pinata

    2016-01-01

    In this paper, we extend the current research in the recommendation system community by showing that users did attach ethical consideration to items. In an experiment (N = 111) that manipulated several moral factors regarding the potentially harmful content in movies, books, and games, users were asked to evaluate the appropriateness of recommending these items to teenagers and adult couples. Results agreed with previous studies in that gender plays a key role in making moral judgment, especially regarding the ethical appropriateness of an item. The pilot study further identifies degrees of aversion regarding the appeal of these elements in media for ethical recommendations. Based on the study, we propose a user-initiated ethical recommender system to help users pick up morally appropriate items during the post-recommendation process. We believe that the ethical appropriateness of items perceived by end users could predict the trust and credibility of the system.

  14. IRMHD: an implicit radiative and magnetohydrodynamical solver for self-gravitating systems

    Science.gov (United States)

    Hujeirat, A.

    1998-07-01

    The 2D implicit hydrodynamical solver developed by Hujeirat & Rannacher is now modified to include the effects of radiation, magnetic fields and self-gravity in different geometries. The underlying numerical concept is based on the operator splitting approach, and the resulting 2D matrices are inverted using different efficient preconditionings such as ADI (alternating direction implicit), the approximate factorization method and Line-Gauss-Seidel or similar iteration procedures. Second-order finite volume with third-order upwinding and second-order time discretization is used. To speed up convergence and enhance efficiency we have incorporated an adaptive time-step control and monotonic multilevel grid distributions as well as vectorizing the code. Test calculations had shown that it requires only 38 per cent more computational effort than its explicit counterpart, whereas its range of application to astrophysical problems is much larger. For example, strongly time-dependent, quasi-stationary and steady-state solutions for the set of Euler and Navier-Stokes equations can now be sought on a non-linearly distributed and strongly stretched mesh. As most of the numerical techniques used to build up this algorithm have been described by Hujeirat & Rannacher in an earlier paper, we focus in this paper on the inclusion of self-gravity, radiation and magnetic fields. Strategies for satisfying the condition ∇.B=0 in the implicit evolution of MHD flows are given. A new discretization strategy for the vector potential which allows alternating use of the direct method is prescribed. We investigate the efficiencies of several 2D solvers for a Poisson-like equation and compare their convergence rates. We provide a splitting approach for the radiative flux within the FLD (flux-limited diffusion) approximation to enhance consistency and accuracy between regions of different optical depths. The results of some test problems are presented to demonstrate the accuracy and

  15. PRS: PERSONNEL RECOMMENDATION SYSTEM FOR HUGE DATA ANALYSIS USING PORTER STEMMER

    Directory of Open Access Journals (Sweden)

    T N Chiranjeevi

    2016-04-01

    Full Text Available Personal recommendation system is one which gives better and preferential recommendation to the users to satisfy their personalized requirements such as practical applications like Webpage Preferences, Sport Videos preferences, Stock selection based on price, TV preferences, Hotel preferences, books, Mobile phones, CDs and various other products now use recommender systems. The existing Pearson Correlation Coefficient (PCC and item-based algorithm using PCC, are called as UPCC and IPCC respectively. These systems are mainly based on only the rating services and does not consider the user personal preferences, they simply just give the result based on the ratings. As the size of data increases it will give the recommendations based on the top rated services and it will miss out most of user preferences. These are main drawbacks in the existing system which will give same results to the users based on some evaluations and rankings or rating service, they will neglect the user preferences and necessities. To address this problem we propose a new approach called, Personnel Recommendation System (PRS for huge data analysis using Porter Stemmer to solve the above challenges. In the proposed system it provides a personalized service recommendation list to the users and recommends the most useful services to the users which will increase the accuracy and efficiency in searching better services. Particularly, a set of suggestions or keywords are provided to indicate user preferences and we used Collaborative Filtering and Porter Stemmer algorithm which gives a suitable recommendations to the users. In real, the broad experiments are conducted on the huge database which is available in real world, and outcome shows that our proposed personal recommender method extensively improves the precision and efficiency of service recommender system over the KASR method. In our approach mainly consider the user preferences so it will not miss out the any of the data

  16. Studying different tasks of implicit learning across multiple test sessions conducted on the web

    Directory of Open Access Journals (Sweden)

    Werner eSævland

    2016-06-01

    Full Text Available Implicit learning is usually studied through individual performance on a single task, with the most common tasks being Serial Reaction Time task (SRT; Nissen and Bullemer, 1987, Dynamic System Control task (DSC; (Berry and Broadbent, 1984 and artificial Grammar Learning task (AGL; (Reber, 1967. Few attempts have been made to compare performance across different implicit learning tasks within the same experiment. The current experiment was designed study the relationship between performance on the DSC Sugar factory task (Berry and Broadbent, 1984 and the Alternating Serial Reaction Time task (ASRT; (Howard and Howard, 1997. We also addressed another limitation to traditional implicit learning experiments, namely that implicit learning is usually studied in laboratory settings over a restricted time span lasting for less than an hour (Berry and Broadbent, 1984; Nissen and Bullemer, 1987; Reber, 1967. In everyday situations, implicit learning is assumed to involve a gradual accumulation of knowledge across several learning episodes over a larger time span (Norman and Price, 2012. One way to increase the ecological validity of implicit learning experiments could be to present the learning material repeatedly across shorter experimental sessions (Howard and Howard, 1997; Cleeremans and McClelland, 1991. This can most easily be done by using a web-based setup that participants can access from home. We therefore created an online web-based system for measuring implicit learning that could be administered in either single or multiple sessions. Participants (n = 66 were assigned to either a single-session or a multi-session condition. Learning and the degree of conscious awareness of the learned regularities was compared across condition (single vs. multiple sessions and tasks (DSC vs. ASRT. Results showed that learning on the two tasks was not related. However, participants in the multiple sessions condition did show greater improvements in reaction

  17. A Knowledge Based Recommender System with Multigranular Linguistic Information

    Directory of Open Access Journals (Sweden)

    Luis Martinez

    2008-08-01

    Full Text Available Recommender systems are applications that have emerged in the e-commerce area in order to assist users in their searches in electronic shops. These shops usually offer a wide range of items that cover the necessities of a great variety of users. Nevertheless, searching in such a wide range of items could be a very difficult and time-consuming task. Recommender systems assist users to find out suitable items by means of recommendations based on information provided by different sources such as: other users, experts, item features, etc. Most of the recommender systems force users to provide their preferences or necessities using an unique numerical scale of information fixed in advance. In spite of this information is usually related to opinions, tastes and perceptions, therefore, it seems that is usually better expressed in a qualitative way, with linguistic terms, than in a quantitative way, with precise numbers. We propose a Knowledge Based Recommender System that uses the fuzzy linguistic approach to define a flexible framework to capture the uncertainty of the user's preferences. Thus, this framework will allow users to express their necessities in scales closer to their own knowledge, and different from the scale utilized to describe the items.

  18. Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

    DEFF Research Database (Denmark)

    Christiansen, René Boyer; Gynther, Karsten; Petersen, Anne Kristine

    2017-01-01

    The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students’ individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von...... Foerster to shed light on how the educational system has used and understood adaptation. In this context, we point out two different approaches to educational adaptation: 1) students adapting to the educational system and 2) the attempt of the educational system to adapt to students through automatized...... system adaptation and recommendation systems. These different understandings constitute a design framework that is used to analyze two current trends: Adaptive learning systems and learning analytics. Finally, the paper discusses the potential of looking at adaptation as recommendation systems...

  19. Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

    DEFF Research Database (Denmark)

    Christiansen, René Boyer; Gynther, Karsten; Petersen, Anne Kristine

    2017-01-01

    The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students’ individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von...... system adaptation and recommendation systems. These different understandings constitute a design framework that is used to analyze two current trends: Adaptive learning systems and learning analytics. Finally, the paper discusses the potential of looking at adaptation as recommendation systems...... Foerster to shed light on how the educational system has used and understood adaptation. In this context, we point out two different approaches to educational adaptation: 1) students adapting to the educational system and 2) the attempt of the educational system to adapt to students through automatized...

  20. Studies of Implicit Prototype Extraction in Patients with Mild Cognitive Impairment and Early Alzheimer's Disease

    Science.gov (United States)

    Nosofsky, Robert M.; Denton, Stephen E.; Zaki, Safa R.; Murphy-Knudsen, Anne F.; Unverzagt, Frederick W.

    2012-01-01

    Studies of incidental category learning support the hypothesis of an implicit prototype-extraction system that is distinct from explicit memory (Smith, 2008). In those studies, patients with explicit-memory impairments due to damage to the medial-temporal lobe performed normally in implicit categorization tasks (Bozoki, Grossman, & Smith, 2006;…

  1. Mainstream Teachers' Implicit Beliefs about English Language Learners: An Implicit Association Test Study of Teacher Beliefs

    Science.gov (United States)

    Harrison, Jamie; Lakin, Joni

    2018-01-01

    Teacher attitudes toward inclusion of English Learners (ELs) in the mainstream classroom have primarily focused on explicit beliefs as accessed through observation, case studies, and self-report surveys. The authors explore implicit mainstream teacher beliefs about ELs using the newly created Implicit Association Test-EL, with correlations to…

  2. Processing implicit control: evidence from reading times

    Directory of Open Access Journals (Sweden)

    Michael eMcCourt

    2015-10-01

    Full Text Available Sentences such as The ship was sunk to collect the insurance exhibit an unusual form of anaphora, implicit control, where neither anaphor nor antecedent is audible. The nonfinite reason clause has an understood subject, PRO, that is anaphoric; here it may be understood as naming the agent of the event of the host clause. Yet since the host is a short passive, this agent is realized by no audible dependent. The putative antecedent to PRO is therefore implicit, which it normally cannot be. What sorts of representations subserve the comprehension of this dependency? Here we present four self-paced reading time studies directed at this question. Previous work showed no processing cost for implicit versus explicit control, and took this to support the view that PRO is linked syntactically to a silent argument in the passive. We challenge this conclusion by reporting that we also find no processing cost for remote implicit control, as in: The ship was sunk. The reason was to collect the insurance. Here the dependency crosses two independent sentences, and so cannot, we argue, be mediated by syntax. Our Experiments 1-4 examined the processing of both implicit (short passive and explicit (active or long passive control in both local and remote configurations. Experiments 3 and 4 added either three days ago or just in order to the local conditions, to control for the distance between the passive and infinitival verbs, and for the predictability of the reason clause, respectively. We replicate the finding that implicit control does not impose an additional processing cost. But critically we show that remote control does not impose a processing cost either. Reading times at the reason clause were never slower when control was remote. In fact they were always faster. Thus efficient processing of local implicit control cannot show that implicit control is mediated by syntax; nor, in turn, that there is a silent but grammatically active argument in passives.

  3. Implicit self-esteem decreases in adolescence: a cross-sectional study.

    Directory of Open Access Journals (Sweden)

    Huajian Cai

    Full Text Available Implicit self-esteem has remained an active research topic in both the areas of implicit social cognition and self-esteem in recent decades. The purpose of this study is to explore the development of implicit self-esteem in adolescents. A total of 599 adolescents from junior and senior high schools in East China participated in the study. They ranged in age from 11 to 18 years with a mean age of 14.10 (SD = 2.16. The degree of implicit self-esteem was assessed using the Implicit Association Test (IAT with the improved D score as the index. Participants also completed the Rosenberg Self-Esteem Scale (α = 0.77. For all surveyed ages, implicit self-esteem was positively biased, all ts>8.59, all ps<0.001. The simple correlation between implicit self-esteem and age was significant, r =  -.25, p = 1. 10(-10. A regression with implicit self-esteem as the criterion variable, and age, gender, and age × gender interaction as predictors further revealed the significant negative linear relationship between age and implicit self-esteem, β = -0.19, t = -3.20, p = 0.001. However, explicit self-esteem manifested a reverse "U" shape throughout adolescence. Implicit self-esteem in adolescence manifests a declining trend with increasing age, suggesting that it is sensitive to developmental or age-related changes. This finding enriches our understanding of the development of implicit social cognition.

  4. Assessment of implicit sexual associations in non-incarcerated pedophiles.

    Science.gov (United States)

    van Leeuwen, Matthijs L; van Baaren, Rick B; Chakhssi, Farid; Loonen, Marijke G M; Lippman, Maarten; Dijksterhuis, Ap

    2013-11-01

    Offences committed by pedophiles are crimes that evoke serious public concern and outrage. Although recent research using implicit measures has shown promise in detecting deviant sexual associations, the discriminatory and predictive quality of implicit tasks has not yet surpassed traditional assessment methods such as questionnaires and phallometry. The current research extended previous findings by examining whether a combination of two implicit tasks, the Implicit Association Task (IAT) and the Picture Association Task (PAT), was capable of differentiating pedophiles from non-pedophiles, and whether the PAT, which allows separate analysis for male, female, boy and girl stimulus categories, was more sensitive to specific sexual associations in pedophiles than the IAT. A total of 20 male self-reported pedophiles (10 offender and 10 non-offenders) and 20 male self-reported heterosexual controls completed the two implicit measures. Results indicated that the combination of both tasks produced the strongest results to date in detecting implicit pedophilic preferences (AUC = .97). Additionally, the PAT showed promise in decomposing the sexual associations in pedophiles. Interestingly, as there was an equal distribution of offenders and non-offenders in the pedophile group, it was possible to test for implicit association differences between these groups. This comparison showed no clear link between having these implicit sexual associations and actual offending.

  5. Types of high self-esteem and prejudice: how implicit self-esteem relates to ethnic discrimination among high explicit self-esteem individuals.

    Science.gov (United States)

    Jordan, Christian H; Spencer, Steven J; Zanna, Mark P

    2005-05-01

    There is increasing recognition that high self-esteem is heterogeneous. Recent research suggests that individuals who report having high self-esteem (i.e., have high explicit self-esteem) behave more defensively to the extent that they have relatively low implicit self-esteem. The current studies test whether individuals with high explicit self-esteem are more likely to discriminate ethnically, as a defensive technique, to the extent that they have relatively low implicit self-esteem. The results support this prediction. Among participants with high explicit self-esteem, all of whom were threatened by negative performance feedback, those with relatively low implicit self-esteem recommended a more severe punishment for a Native, but not a White, student who started a fist-fight. In Study 2, this pattern was not apparent for participants with relatively low explicit self-esteem.

  6. Intelligent Online Store: User Behavior Analysis based Recommender System

    Directory of Open Access Journals (Sweden)

    Mohamadreza Karimi Alavije

    2015-06-01

    Full Text Available Recommender systems provide personalised recommendations to users, helping them find their ideal items, also play a key role in encouraging users to make their purchases through websites thus leading to the success of online stores. The collaborative filtering method is one of the most successful techniques utilized in these systems facilitating the provision of recommendations close to that of the customer's taste and need. However the proliferation of both customers and products on offer, the technique faces some issues such as "cold start" and scalability. As such in this paper a new method has been introduced in which user-based collaborative filtering is used at a base method along with a weighted clustering of users based upon demographics in order to improve the results obtained from the system. The implementation of the results of the algorithms demonstrate that the presented approach has a lower RMSE, which means that the system offers improved performance and accuracy and that the resulting recommendations are closer to the taste and preferences of the users.

  7. A recommender system for prostate cancer websites.

    Science.gov (United States)

    Witteman, Holly; Chignell, Mark; Krahn, Murray

    2008-11-06

    One of the challenges for people seeking health information online is the difficulty in locating health Websites that are personally relevant, credible and useful. We developed a Web-based recommender system in order to help address this problem in the context of prostate cancer. We are conducting an online randomized controlled trial to evaluate the accuracy of its recommendations and to compare the efficacy of content-based and collaborative filtering.

  8. Implicit attitudes towards risky and safe driving

    DEFF Research Database (Denmark)

    Martinussen, Laila Marianne; Sømhovd, Mikael Julius; Møller, Mette

    ; further, self-reports of the intention to drive safely (or not) are socially sensitive. Therefore, we examined automatic preferences towards safe and risky driving with a Go/No-go Association Task (GNAT). The results suggest that (1) implicit attitudes towards driving behavior can be measured reliably...... with the GNAT; (2) implicit attitudes towards safe driving versus towards risky driving may be separable constructs. We propose that research on driving behavior may benefit from routinely including measures of implicit cognition. A practical advantage is a lesser susceptibility to social desirability biases......, compared to self-report methods. Pending replication in future research, the apparent dissociation between implicit attitudes towards safe versus risky driving that we observed may contribute to a greater theoretical understanding of the causes of unsafe and risky driving behavior....

  9. Unconscious Motivation. Part I: Implicit Attitudes toward L2 Speakers

    Science.gov (United States)

    Al-Hoorie, Ali H.

    2016-01-01

    This paper reports the first investigation in the second language acquisition field assessing learners' implicit attitudes using the Implicit Association Test, a computerized reaction-time measure. Examination of the explicit and implicit attitudes of Arab learners of English (N = 365) showed that, particularly for males, implicit attitudes toward…

  10. The Implicit Relational Assessment Procedure as a Measure of Implicit Depression and the Role of Psychological Flexibility

    Science.gov (United States)

    Hussey, Ian; Barnes-Holmes, Dermot

    2012-01-01

    A broad implicit measure of depressive emotional reactions was created by mapping the content of the depression scale from the Depression Anxiety and Stress Scale (DASS) on to the Implicit Relational Assessment Procedure (IRAP). Participants were asked to relate pairings of antecedents and emotional reactions that followed the formula "When X…

  11. A Stock Trading Recommender System Based on Temporal Association Rule Mining

    Directory of Open Access Journals (Sweden)

    Binoy B. Nair

    2015-04-01

    Full Text Available Recommender systems capable of discovering patterns in stock price movements and generating stock recommendations based on the patterns thus discovered can significantly supplement the decision-making process of a stock trader. Such recommender systems are of great significance to a layperson who wishes to profit by stock trading even while not possessing the skill or expertise of a seasoned trader. A genetic algorithm optimized Symbolic Aggregate approXimation (SAX–Apriori based stock trading recommender system, which can mine temporal association rules from the stock price data set to generate stock trading recommendations, is presented in this article. The proposed system is validated on 12 different data sets. The results indicate that the proposed system significantly outperforms the passive buy-and-hold strategy, offering scope for a layperson to successfully invest in capital markets.

  12. Consumers’ intention to use health recommendation systems to receive personalized nutrition advice

    Science.gov (United States)

    2013-01-01

    Background Sophisticated recommendation systems are used more and more in the health sector to assist consumers in healthy decision making. In this study we investigate consumers' evaluation of hypothetical health recommendation systems that provide personalized nutrition advice. We examine consumers' intention to use such a health recommendation system as a function of options related to the underlying system (e.g. the type of company that generates the advice) as well as intermediaries (e.g. general practitioner) that might assist in using the system. We further explore if the effect of both the system and intermediaries on intention to use a health recommendation system are mediated by consumers' perceived effort, privacy risk, usefulness and enjoyment. Methods 204 respondents from a consumer panel in the Netherlands participated. The data were collected by means of a questionnaire. Each respondent evaluated three hypothetical health recommendation systems on validated multi-scale measures of effort, privacy risk, usefulness, enjoyment and intention to use the system. To test the hypothesized relationships we used regression analyses. Results We find evidence that the options related to the underlying system as well as the intermediaries involved influence consumers' intention to use such a health recommendation system and that these effects are mediated by perceptions of effort, privacy risk, usefulness and enjoyment. Also, we find that consumers value usefulness of a system more and enjoyment less when a general practitioner advices them to use a health recommendation system than if they use it out of their own curiosity. Conclusions We developed and tested a model of consumers' intention to use a health recommendation system. We found that intermediaries play an important role in how consumers evaluate such a system over and above options of the underlying system that is used to generate the recommendation. Also, health-related information services seem to

  13. Consumers' intention to use health recommendation systems to receive personalized nutrition advice.

    Science.gov (United States)

    Wendel, Sonja; Dellaert, Benedict G C; Ronteltap, Amber; van Trijp, Hans C M

    2013-04-04

    Sophisticated recommendation systems are used more and more in the health sector to assist consumers in healthy decision making. In this study we investigate consumers' evaluation of hypothetical health recommendation systems that provide personalized nutrition advice. We examine consumers' intention to use such a health recommendation system as a function of options related to the underlying system (e.g. the type of company that generates the advice) as well as intermediaries (e.g. general practitioner) that might assist in using the system. We further explore if the effect of both the system and intermediaries on intention to use a health recommendation system are mediated by consumers' perceived effort, privacy risk, usefulness and enjoyment. 204 respondents from a consumer panel in the Netherlands participated. The data were collected by means of a questionnaire. Each respondent evaluated three hypothetical health recommendation systems on validated multi-scale measures of effort, privacy risk, usefulness, enjoyment and intention to use the system. To test the hypothesized relationships we used regression analyses. We find evidence that the options related to the underlying system as well as the intermediaries involved influence consumers' intention to use such a health recommendation system and that these effects are mediated by perceptions of effort, privacy risk, usefulness and enjoyment. Also, we find that consumers value usefulness of a system more and enjoyment less when a general practitioner advices them to use a health recommendation system than if they use it out of their own curiosity. We developed and tested a model of consumers' intention to use a health recommendation system. We found that intermediaries play an important role in how consumers evaluate such a system over and above options of the underlying system that is used to generate the recommendation. Also, health-related information services seem to rely on endorsement by the medical sector

  14. Location-aware News Recommendation System with Using Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Mehdi Nejati

    2016-10-01

    Full Text Available with release of a huge amount of news on the Internet and the trend of users to Web-based news services.it is necessary to have a recommendation system. To grab attentions to news, news services use a number of criteria that called news values and user location is an important factor for it. In this paper, LONEF is proposed as a tow stage recommendation system. In first stage news are ranked by user’s locations and in second stage news are recommended by location Preferences, recency, Trustworthiness, groups priorities and popularity. To reduce ambiguity these properties is used tow Mamdani fuzzy interference and case-based decision systems. In Mamdani fuzzy interference system, it is tried to increase the system speed by optimizing selection of rules and membership functions and because of ambiguous feedback implementation, a decision making system is used to enable better simulation of user’s activities. Performance of our proposed approach is demonstrated in the experiments on different news groups.

  15. NN-Based Implicit Stochastic Optimization of Multi-Reservoir Systems Management

    Directory of Open Access Journals (Sweden)

    Matteo Sangiorgio

    2018-03-01

    Full Text Available Multi-reservoir systems management is complex because of the uncertainty on future events and the variety of purposes, usually conflicting, of the involved actors. An efficient management of these systems can help improving resource allocation, preventing political crisis and reducing the conflicts between the stakeholders. Bellman stochastic dynamic programming (SDP is the most famous among the many proposed approaches to solve this optimal control problem. Unfortunately, SDP is affected by the curse of dimensionality: computational effort increases exponentially with the complexity of the considered system (i.e., number of reservoirs, and the problem rapidly becomes intractable. This paper proposes an implicit stochastic optimization approach for the solution of the reservoir management problem. The core idea is using extremely flexible functions, such as artificial neural networks (NN, for designing release rules which approximate the optimal policies obtained by an open-loop approach. These trained NNs can then be used to take decisions in real time. The approach thus requires a sufficiently long series of historical or synthetic inflows, and the definition of a compromise solution to be approximated. This work analyzes with particular emphasis the importance of the information which represents the input of the control laws, investigating the effects of different degrees of completeness. The methodology is applied to the Nile River basin considering the main management objectives (minimization of the irrigation water deficit and maximization of the hydropower production, but can be easily adopted also in other cases.

  16. Implicit self-esteem decreases in adolescence: a cross-sectional study.

    Science.gov (United States)

    Cai, Huajian; Wu, Mingzheng; Luo, Yu L L; Yang, Jing

    2014-01-01

    Implicit self-esteem has remained an active research topic in both the areas of implicit social cognition and self-esteem in recent decades. The purpose of this study is to explore the development of implicit self-esteem in adolescents. A total of 599 adolescents from junior and senior high schools in East China participated in the study. They ranged in age from 11 to 18 years with a mean age of 14.10 (SD = 2.16). The degree of implicit self-esteem was assessed using the Implicit Association Test (IAT) with the improved D score as the index. Participants also completed the Rosenberg Self-Esteem Scale (α = 0.77). For all surveyed ages, implicit self-esteem was positively biased, all ts>8.59, all psself-esteem and age was significant, r =  -.25, p = 1. 10(-10). A regression with implicit self-esteem as the criterion variable, and age, gender, and age × gender interaction as predictors further revealed the significant negative linear relationship between age and implicit self-esteem, β = -0.19, t = -3.20, p = 0.001. However, explicit self-esteem manifested a reverse "U" shape throughout adolescence. Implicit self-esteem in adolescence manifests a declining trend with increasing age, suggesting that it is sensitive to developmental or age-related changes. This finding enriches our understanding of the development of implicit social cognition.

  17. The sensorimotor contributions to implicit memory, familiarity, and recollection.

    Science.gov (United States)

    Topolinski, Sascha

    2012-05-01

    The sensorimotor contributions to memory for prior occurrence were investigated. Previous research has shown that both implicit memory and familiarity draw on gains in stimulus-related processing fluency for old, compared with novel, stimuli, but recollection does not. Recently, it has been demonstrated that processing fluency itself resides in stimulus-specific motor simulations or reenactment (e.g., covert pronouncing simulations for words as stimuli). Combining these lines of evidence, it was predicted that stimulus-specific motor interference preventing simulations should impair both implicit memory and familiarity but leave recollection unaffected. This was tested for words as verbal stimuli associated to pronouncing simulations in the oral muscle system (but also for tunes as vocal stimuli and their associated vocal system, Experiment 2). It was found that oral (e.g., chewing gum), compared with manual (kneading a ball), motor interference prevented mere exposure effects (Experiments 1-2), substantially reduced repetition priming in word fragment completion (Experiment 3), reduced the familiarity estimates in a remember-know task (Experiment 5) and in receiver-operating characteristics (Experiment 6), and completely neutralized familiarity measured by self-reports (Experiment 4) and skin conductance responses (Experiment 7), while leaving recollection and free recall unaffected (across Experiments 1-7). This pattern establishes a rare memory dissociation in healthy participants, that is, explicit without implicit memory or recognizing without feeling familiar. Implications for embodied memory and neuropsychology are discussed.

  18. Implicit time accurate simulation of unsteady flow

    Science.gov (United States)

    van Buuren, René; Kuerten, Hans; Geurts, Bernard J.

    2001-03-01

    Implicit time integration was studied in the context of unsteady shock-boundary layer interaction flow. With an explicit second-order Runge-Kutta scheme, a reference solution to compare with the implicit second-order Crank-Nicolson scheme was determined. The time step in the explicit scheme is restricted by both temporal accuracy as well as stability requirements, whereas in the A-stable implicit scheme, the time step has to obey temporal resolution requirements and numerical convergence conditions. The non-linear discrete equations for each time step are solved iteratively by adding a pseudo-time derivative. The quasi-Newton approach is adopted and the linear systems that arise are approximately solved with a symmetric block Gauss-Seidel solver. As a guiding principle for properly setting numerical time integration parameters that yield an efficient time accurate capturing of the solution, the global error caused by the temporal integration is compared with the error resulting from the spatial discretization. Focus is on the sensitivity of properties of the solution in relation to the time step. Numerical simulations show that the time step needed for acceptable accuracy can be considerably larger than the explicit stability time step; typical ratios range from 20 to 80. At large time steps, convergence problems that are closely related to a highly complex structure of the basins of attraction of the iterative method may occur. Copyright

  19. Assessing Implicit Knowledge in BIM Models with Machine Learning

    DEFF Research Database (Denmark)

    Krijnen, Thomas; Tamke, Martin

    2015-01-01

    architects and engineers are able to deduce non-explicitly explicitly stated information, which is often the core of the transported architectural information. This paper investigates how machine learning approaches allow a computational system to deduce implicit knowledge from a set of BIM models....

  20. A Multimodal Database for Affect Recognition and Implicit Tagging

    NARCIS (Netherlands)

    Soleymani, Mohammad; Lichtenauer, Jeroen; Pun, Thierry; Pantic, Maja

    MAHNOB-HCI is a multimodal database recorded in response to affective stimuli with the goal of emotion recognition and implicit tagging research. A multimodal setup was arranged for synchronized recording of face videos, audio signals, eye gaze data, and peripheral/central nervous system

  1. Implicit Consensus: Blockchain with Unbounded Throughput

    OpenAIRE

    Ren, Zhijie; Cong, Kelong; Pouwelse, Johan; Erkin, Zekeriya

    2017-01-01

    Recently, the blockchain technique was put in the spotlight as it introduced a systematic approach for multiple parties to reach consensus without needing trust. However, the application of this technique in practice is severely restricted due to its limitations in throughput. In this paper, we propose a novel consensus model, namely the implicit consensus, with a distinctive blockchain-based distributed ledger in which each node holds its individual blockchain. In our system, the consensus i...

  2. The implicit function theorem history, theory, and applications

    CERN Document Server

    Krantz, Steven G

    2003-01-01

    The implicit function theorem is part of the bedrock of mathematics analysis and geometry. Finding its genesis in eighteenth century studies of real analytic functions and mechanics, the implicit and inverse function theorems have now blossomed into powerful tools in the theories of partial differential equations, differential geometry, and geometric analysis. There are many different forms of the implicit function theorem, including (i) the classical formulation for Ck functions, (ii) formulations in other function spaces, (iii) formulations for non-smooth function, (iv) formulations for functions with degenerate Jacobian. Particularly powerful implicit function theorems, such as the Nash-Moser theorem, have been developed for specific applications (e.g., the imbedding of Riemannian manifolds). All of these topics, and many more, are treated in the present volume. The history of the implicit function theorem is a lively and complex store, and intimately bound up with the development of fundamental ideas in a...

  3. Information filtering in sparse online systems: recommendation via semi-local diffusion.

    Science.gov (United States)

    Zeng, Wei; Zeng, An; Shang, Ming-Sheng; Zhang, Yi-Cheng

    2013-01-01

    With the rapid growth of the Internet and overwhelming amount of information and choices that people are confronted with, recommender systems have been developed to effectively support users' decision-making process in the online systems. However, many recommendation algorithms suffer from the data sparsity problem, i.e. the user-object bipartite networks are so sparse that algorithms cannot accurately recommend objects for users. This data sparsity problem makes many well-known recommendation algorithms perform poorly. To solve the problem, we propose a recommendation algorithm based on the semi-local diffusion process on the user-object bipartite network. The simulation results on two sparse datasets, Amazon and Bookcross, show that our method significantly outperforms the state-of-the-art methods especially for those small-degree users. Two personalized semi-local diffusion methods are proposed which further improve the recommendation accuracy. Finally, our work indicates that sparse online systems are essentially different from the dense online systems, so it is necessary to reexamine former algorithms and conclusions based on dense data in sparse systems.

  4. An Extended-Tag-Induced Matrix Factorization Technique for Recommender Systems

    Directory of Open Access Journals (Sweden)

    Huirui Han

    2018-06-01

    Full Text Available Social tag information has been used by recommender systems to handle the problem of data sparsity. Recently, the relationships between users/items and tags are considered by most tag-induced recommendation methods. However, sparse tag information is challenging to most existing methods. In this paper, we propose an Extended-Tag-Induced Matrix Factorization technique for recommender systems, which exploits correlations among tags derived by co-occurrence of tags to improve the performance of recommender systems, even in the case of sparse tag information. The proposed method integrates coupled similarity between tags, which is calculated by the co-occurrences of tags in the same items, to extend each item’s tags. Finally, item similarity based on extended tags is utilized as an item relationship regularization term to constrain the process of matrix factorization. MovieLens dataset and Book-Crossing dataset are adopted to evaluate the performance of the proposed algorithm. The results of experiments show that the proposed method can alleviate the impact of tag sparsity and improve the performance of recommender systems.

  5. The implicit contract: implications for health social work.

    Science.gov (United States)

    McCoyd, Judith L M

    2010-05-01

    Identifying common patient dynamics is useful for developing social work practice sensitivity in health social work. This article draws on findings from a study of women who terminated desired pregnancies because of fetal anomalies and identifies dynamics that may be applicable to many health settings. Data suggest that women have expectations that submission to medical care, particularly high-tech medical care, should ensure a positive outcome--in this case a healthy baby. Analysis of data reveals the presence of an implicit contract that the women hold with the medical system,"Mother Nature," or society. The analysis carries an implication that health social work should help patients develop realistic expectations about health care. The presence of implicit contracts may have further implications for liability and litigation. Social work roles and interventions are addressed.

  6. An in-depth stability analysis of nonuniform FDTD combined with novel local implicitization techniques

    Science.gov (United States)

    Van Londersele, Arne; De Zutter, Daniël; Vande Ginste, Dries

    2017-08-01

    This work focuses on efficient full-wave solutions of multiscale electromagnetic problems in the time domain. Three local implicitization techniques are proposed and carefully analyzed in order to relax the traditional time step limit of the Finite-Difference Time-Domain (FDTD) method on a nonuniform, staggered, tensor product grid: Newmark, Crank-Nicolson (CN) and Alternating-Direction-Implicit (ADI) implicitization. All of them are applied in preferable directions, alike Hybrid Implicit-Explicit (HIE) methods, as to limit the rank of the sparse linear systems. Both exponential and linear stability are rigorously investigated for arbitrary grid spacings and arbitrary inhomogeneous, possibly lossy, isotropic media. Numerical examples confirm the conservation of energy inside a cavity for a million iterations if the time step is chosen below the proposed, relaxed limit. Apart from the theoretical contributions, new accomplishments such as the development of the leapfrog Alternating-Direction-Hybrid-Implicit-Explicit (ADHIE) FDTD method and a less stringent Courant-like time step limit for the conventional, fully explicit FDTD method on a nonuniform grid, have immediate practical applications.

  7. Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks

    KAUST Repository

    Ben Hammouda, Chiheb

    2015-05-12

    In biochemical systems, stochastic e↵ects can be caused by the presence of small numbers of certain reactant molecules. In this setting, discrete state-space and stochastic simulation approaches were proved to be more relevant than continuous state-space and deterministic ones. These stochastic models constitute the theory of stochastic reaction networks (SRNs). Furthermore, in some cases, the dynamics of fast and slow time scales can be well separated and this is characterized by what is called sti↵ness. For such problems, the existing discrete space-state stochastic path simulation methods, such as the stochastic simulation algorithm (SSA) and the explicit tau-leap method, can be very slow. Therefore, implicit tau-leap approxima- tions were developed to improve the numerical stability and provide more e cient simulation algorithms for these systems. One of the interesting tasks for SRNs is to approximate the expected values of some observables of the process at a certain fixed time T. This is can be achieved using Monte Carlo (MC) techniques. However, in a recent work, Anderson and Higham in 2013, proposed a more computationally e cient method which combines multi-level Monte Carlo (MLMC) technique with explicit tau-leap schemes. In this MSc thesis, we propose new fast stochastic algorithm, particularly designed 5 to address sti↵ systems, for approximating the expected values of some observables of SRNs. In fact, we take advantage of the idea of MLMC techniques and drift-implicit tau-leap approximation to construct a drift-implicit MLMC tau-leap estimator. In addition to accurately estimating the expected values of a given observable of SRNs at a final time T , our proposed estimator ensures the numerical stability with a lower cost than the MLMC explicit tau-leap algorithm, for systems including simultane- ously fast and slow species. The key contribution of our work is the coupling of two drift-implicit tau-leap paths, which is the basic brick for

  8. Implicit Self-Esteem Decreases in Adolescence: A Cross-Sectional Study

    Science.gov (United States)

    Cai, Huajian; Wu, Mingzheng; Luo, Yu L. L.; Yang, Jing

    2014-01-01

    Implicit self-esteem has remained an active research topic in both the areas of implicit social cognition and self-esteem in recent decades. The purpose of this study is to explore the development of implicit self-esteem in adolescents. A total of 599 adolescents from junior and senior high schools in East China participated in the study. They ranged in age from 11 to 18 years with a mean age of 14.10 (SD = 2.16). The degree of implicit self-esteem was assessed using the Implicit Association Test (IAT) with the improved D score as the index. Participants also completed the Rosenberg Self-Esteem Scale (α = 0.77). For all surveyed ages, implicit self-esteem was positively biased, all ts>8.59, all psself-esteem and age was significant, r = −.25, p = 1.0×10−10. A regression with implicit self-esteem as the criterion variable, and age, gender, and age × gender interaction as predictors further revealed the significant negative linear relationship between age and implicit self-esteem, β = −0.19, t = −3.20, p = 0.001. However, explicit self-esteem manifested a reverse “U” shape throughout adolescence. Implicit self-esteem in adolescence manifests a declining trend with increasing age, suggesting that it is sensitive to developmental or age-related changes. This finding enriches our understanding of the development of implicit social cognition. PMID:24587169

  9. Extending a Hybrid Tag-Based Recommender System with Personalization

    DEFF Research Database (Denmark)

    Durao, Frederico; Dolog, Peter

    2010-01-01

    extension for a hybrid tag-based recommender system, which suggests similar Web pages based on the similarity of their tags. The semantic extension aims at discovering tag relations which are not considered in basic syntax similarity. With the goal of generating more semantically grounded recommendations......, the proposal extends a hybrid tag-based recommender system with a semantic factor, which looks for tag relations in different semantic sources. In order to evaluate the benefits acquired with the semantic extension, we have compared the new findings with results from a previous experiment involving 38 people......Tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. Tags themselves can be therefore used for finding personalized recommendations of items. This paper proposes a semantic...

  10. Media multitasking and implicit learning.

    Science.gov (United States)

    Edwards, Kathleen S; Shin, Myoungju

    2017-07-01

    Media multitasking refers to the simultaneous use of different forms of media. Previous research comparing heavy media multitaskers and light media multitaskers suggests that heavy media multitaskers have a broader scope of attention. The present study explored whether these differences in attentional scope would lead to a greater degree of implicit learning for heavy media multitaskers. The study also examined whether media multitasking behaviour is associated with differences in visual working memory, and whether visual working memory differentially affects the ability to process contextual information. In addition to comparing extreme groups (heavy and light media multitaskers) the study included analysis of people who media multitask in moderation (intermediate media multitaskers). Ninety-four participants were divided into groups based on responses to the media use questionnaire, and completed the contextual cueing and n-back tasks. Results indicated that the speed at which implicit learning occurred was slower in heavy media multitaskers relative to both light and intermediate media multitaskers. There was no relationship between working memory performance and media multitasking group, and no relationship between working memory and implicit learning. There was also no evidence for superior performance of intermediate media multitaskers. A deficit in implicit learning observed in heavy media multitaskers is consistent with previous literature, which suggests that heavy media multitaskers perform more poorly than light media multitaskers in attentional tasks due to their wider attentional scope.

  11. White and Black American Children’s Implicit Intergroup Bias

    Science.gov (United States)

    Newheiser, Anna-Kaisa; Olson, Kristina R.

    2011-01-01

    Despite a decline in explicit prejudice, adults and children from majority groups (e.g., White Americans) often express bias implicitly, as assessed by the Implicit Association Test. In contrast, minority-group (e.g., Black American) adults on average show no bias on the IAT. In the present research, representing the first empirical investigation of whether Black children’s IAT responses parallel those of Black adults, we examined implicit bias in 7–11-year-old White and Black American children. Replicating previous findings with adults, whereas White children showed a robust ingroup bias, Black children showed no bias. Additionally, we investigated the role of valuing status in the development of implicit bias. For Black children, explicit preference for high status predicted implicit outgroup bias: Black children who explicitly expressed high preference for rich (vs. poor) people showed an implicit preference for Whites comparable in magnitude to White children’s ingroup bias. Implications for research on intergroup bias are discussed. PMID:22184478

  12. A LITERATURE SURVEY ON RECOMMENDATION SYSTEM BASED ON SENTIMENTAL ANALYSIS

    OpenAIRE

    Achin Jain; Vanita Jain; Nidhi Kapoor

    2016-01-01

    Recommender systems have grown to be a critical research subject after the emergence of the first paper on collaborative filtering in the Nineties. Despite the fact that educational studies on recommender systems, has extended extensively over the last 10 years, there are deficiencies in the complete literature evaluation and classification of that research. Because of this, we reviewed articles on recommender structures, and then classified those based on sentiment analysis. The articles are...

  13. How Recommender Systems in Technology-Enhanced Learning depend on Context

    NARCIS (Netherlands)

    Drachsler, Hendrik; Manouselis, Nikos

    2009-01-01

    Drachsler, H., & Manouselis, N. (2009). How Recommender Systems in Technology-Enhanced Learning depend on Context. Presentation given at the 1st workshop on Context-aware Recommender Systems for Learning at the Alpine Rendez-Vous 2009. November, 30 - December, 3, 2009, Garmisch-Patenkirchen,

  14. Implicit Self-Esteem Decreases in Adolescence: A Cross-Sectional Study

    OpenAIRE

    Cai, Huajian; Wu, Mingzheng; Luo, Yu L. L.; Yang, Jing

    2014-01-01

    Implicit self-esteem has remained an active research topic in both the areas of implicit social cognition and self-esteem in recent decades. The purpose of this study is to explore the development of implicit self-esteem in adolescents. A total of 599 adolescents from junior and senior high schools in East China participated in the study. They ranged in age from 11 to 18 years with a mean age of 14.10 (SD = 2.16). The degree of implicit self-esteem was assessed using the Implicit Association ...

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

    Directory of Open Access Journals (Sweden)

    Mohamed FRIKHA

    2015-12-01

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

  16. Towards a theoretical foundation for explicitation and implicitation

    OpenAIRE

    De Metsenaere, Hinde; Vandepitte, Sonia

    2017-01-01

    Explicitation and implicitation are two translation studies concepts that have given rise to a vast array of studies. These studies are, however, often difficult to compare, primarily because explicitation and implicitation have been interpreted differently, not rarely intuitively, by many translation studies researchers. This is due to the fact that the underlying concepts of explicitness and implicitness have not yet been satisfactorily defined for translation studies purposes. It is there...

  17. Globalized Newton-Krylov-Schwarz Algorithms and Software for Parallel Implicit CFD

    Science.gov (United States)

    Gropp, W. D.; Keyes, D. E.; McInnes, L. C.; Tidriri, M. D.

    1998-01-01

    Implicit solution methods are important in applications modeled by PDEs with disparate temporal and spatial scales. Because such applications require high resolution with reasonable turnaround, "routine" parallelization is essential. The pseudo-transient matrix-free Newton-Krylov-Schwarz (Psi-NKS) algorithmic framework is presented as an answer. We show that, for the classical problem of three-dimensional transonic Euler flow about an M6 wing, Psi-NKS can simultaneously deliver: globalized, asymptotically rapid convergence through adaptive pseudo- transient continuation and Newton's method-, reasonable parallelizability for an implicit method through deferred synchronization and favorable communication-to-computation scaling in the Krylov linear solver; and high per- processor performance through attention to distributed memory and cache locality, especially through the Schwarz preconditioner. Two discouraging features of Psi-NKS methods are their sensitivity to the coding of the underlying PDE discretization and the large number of parameters that must be selected to govern convergence. We therefore distill several recommendations from our experience and from our reading of the literature on various algorithmic components of Psi-NKS, and we describe a freely available, MPI-based portable parallel software implementation of the solver employed here.

  18. The Use of Hypermedia in Implicit Vocabulary Learning

    Directory of Open Access Journals (Sweden)

    Patrícia Nora de Souza

    2011-07-01

    Full Text Available The present work is aimed at investigating the role of hypermedia in implicit vocabulary acquisition in foreign language. On theoretical grounds, the work presents a reflection which contextualizes the discussion on implicit approaches to vocabulary teaching. Besides, a review and a discussion of the literature is carried out, with regard to the advantages of hypermedia in English Language Teaching. Following that, the selection of hypermedia material for implicit vocabulary teaching is presented. This material was used in the data collecting which comprised 75 students. The material was evaluated by the students through a questionnaire. The results show that the use of hypermedia can significantly contribute to implicit vocabulary acquisition.

  19. Personalized links recommendation based on data mining in adaptive educational hypermedia systems

    NARCIS (Netherlands)

    Romero, C.; Ventura, S.; Delgado, J.A.; De Bra, P.M.E.; Duval, E.; Klamma, R.; Wolpers, M.

    2007-01-01

    In this paper, we describe a personalized recommender system that uses web mining techniques for recommending a student which (next) links to visit within an adaptable educational hypermedia system. We present a specific mining tool and a recommender engine that we have integrated in the AHA! system

  20. Recommendations to alarm systems and lessons learned on alarm system implementation

    International Nuclear Information System (INIS)

    Soerenssen, Aimar; Veland, Oeystein; Farbrot, Jan Erik; Kaarstad, Magnhild; Seim, Lars Aage; Foerdestroemmen, Nils; Bye, Andreas

    2001-11-01

    Alarm systems have been of major concern within complex industrial processes for many years. Within the nuclear community, the TMI accident in 1979 was the first really serious event that showed also the importance of the man-machine aspects of the systems in general, and the alarm system in particular. The OECD Halden Reactor Project has been working with alarm systems since 1974. This report is an attempt to gather some of the knowledge that has been accumulated during the years in Halden, both in research and also in bilateral projects. Bilateral projects within this field have provided a practical basis of knowledge.A major part of this report consists of a set of recommendations, which reflect HRP's current understanding of how an alarm system should work. There are also recommendations on design methods. But also other issues are included, as system development and implementation experience, and experimental knowledge on the performance of alarm systems. Some open issues are also discussed. (Author). 54 refs., 15 figs

  1. An Interactive Personalized Recommendation System Using the Hybrid Algorithm Model

    Directory of Open Access Journals (Sweden)

    Yan Guo

    2017-10-01

    Full Text Available With the rapid development of e-commerce, the contradiction between the disorder of business information and customer demand is increasingly prominent. This study aims to make e-commerce shopping more convenient, and avoid information overload, by an interactive personalized recommendation system using the hybrid algorithm model. The proposed model first uses various recommendation algorithms to get a list of original recommendation results. Combined with the customer’s feedback in an interactive manner, it then establishes the weights of corresponding recommendation algorithms. Finally, the synthetic formula of evidence theory is used to fuse the original results to obtain the final recommendation products. The recommendation performance of the proposed method is compared with that of traditional methods. The results of the experimental study through a Taobao online dress shop clearly show that the proposed method increases the efficiency of data mining in the consumer coverage, the consumer discovery accuracy and the recommendation recall. The hybrid recommendation algorithm complements the advantages of the existing recommendation algorithms in data mining. The interactive assigned-weight method meets consumer demand better and solves the problem of information overload. Meanwhile, our study offers important implications for e-commerce platform providers regarding the design of product recommendation systems.

  2. Implicit Referential Meaning with Reference to English Arabic Translation

    Science.gov (United States)

    Al-Zughoul, Basem

    2014-01-01

    The purpose of this study is to investigate how English implicit referential meaning is translated into Arabic by analyzing sentences containing implicit referential meanings found in the novel "Harry Potter and the Prisoner of Azkaban". The analysis shows that the translation of English implicit referential meaning into Arabic can be…

  3. On the Reliability of Implicit and Explicit Memory Measures.

    Science.gov (United States)

    Buchner, Axel; Wippich, Werner

    2000-01-01

    Studied the reliability of implicit and explicit memory tests in experiments involving these tests. Results with 168, 84, 120, and 128 undergraduates show that methodological artifacts may cause implicit memory tests to have lower reliability than explicit memory tests, but that implicit tests need not necessarily be less reliable. (SLD)

  4. Implicit Attitudes toward the Self Over Time in Chinese Undergraduates

    Directory of Open Access Journals (Sweden)

    Qing Yang

    2017-10-01

    Full Text Available Although the explicit attitudes of Chinese people toward the self over time are known (i.e., past = present < future, little is known about their implicit attitudes. Two studies were conducted to measure the implicit subjective temporal trajectory (STT of Chinese undergraduates. Study 1 used a Go/No-go association task to measure participants’ implicit attitudes toward their past, present, and future selves. The obtained implicit STT was different from the explicit pattern found in former research. It showed that the future self was viewed to be identical to the present self and participants implicitly evaluated their present self as better than the past self. Since this comparison of the past and present selves suggested a cultural difference, we aimed to replicate this finding in Study 2. Using an implicit association test, we again found that the present self was more easily associated with positive valence than the past self. Overall, both studies reveal an implicitly inclining-flat STT (i.e., past < present = future for Chinese undergraduates. Implications of this difference in explicit-implicit measures and the cultural differences of temporal self appraisals are discussed.

  5. A Framework for Integrating Implicit Bias Recognition Into Health Professions Education.

    Science.gov (United States)

    Sukhera, Javeed; Watling, Chris

    2018-01-01

    Existing literature on implicit bias is fragmented and comes from a variety of fields like cognitive psychology, business ethics, and higher education, but implicit-bias-informed educational approaches have been underexplored in health professions education and are difficult to evaluate using existing tools. Despite increasing attention to implicit bias recognition and management in health professions education, many programs struggle to meaningfully integrate these topics into curricula. The authors propose a six-point actionable framework for integrating implicit bias recognition and management into health professions education that draws on the work of previous researchers and includes practical tools to guide curriculum developers. The six key features of this framework are creating a safe and nonthreatening learning context, increasing knowledge about the science of implicit bias, emphasizing how implicit bias influences behaviors and patient outcomes, increasing self-awareness of existing implicit biases, improving conscious efforts to overcome implicit bias, and enhancing awareness of how implicit bias influences others. Important considerations for designing implicit-bias-informed curricula-such as individual and contextual variables, as well as formal and informal cultural influences-are discussed. The authors also outline assessment and evaluation approaches that consider outcomes at individual, organizational, community, and societal levels. The proposed framework may facilitate future research and exploration regarding the use of implicit bias in health professions education.

  6. Social and Behavioral Aspects of a Tag-Based Recommender System

    DEFF Research Database (Denmark)

    Durao, Frederico; Dolog, Peter

    2009-01-01

    Collaborative tagging has emerged as a useful means to organize and share resources on the Web. Recommender systems have been utilized tags for identifying similar resources and generate personalized recommendations. In this paper, we analyze social and behavioral aspects of a tag-based recommender...... system which suggests similar Web pages based on the similarity of their tags. Tagging behavior and language anomalies in tagging activities are some aspects examined from an experiment involving 38 people from 12 countries....

  7. A Personalized Tag-Based Recommendation in Social Web Systems

    DEFF Research Database (Denmark)

    Durao, Frederico; Dolog, Peter

    2009-01-01

    -based recommender system which suggests similar Web pages based on the similarity of their tags from a Web 2.0 tagging application. The proposed approach extends the basic similarity calculus with external factors such as tag popularity, tag representativeness and the affinity between user and tag. In order...... to study and evaluate the recommender system, we have conducted an experiment involving 38 people from 12 countries using data from Del.icio.us , a social bookmarking web system on which users can share their personal bookmarks......Tagging activity has been recently identified as a potential source of knowledge about personal interests, preferences, goals, and other attributes known from user models. Tags themselves can be therefore used for finding personalized recommendations of items. In this paper, we present a tag...

  8. The Use of Hypermedia in Implicit Vocabulary Learning

    OpenAIRE

    Patrícia Nora de Souza

    2011-01-01

    The present work is aimed at investigating the role of hypermedia in implicit vocabulary acquisition in foreign language. On theoretical grounds, the work presents a reflection which contextualizes the discussion on implicit approaches to vocabulary teaching. Besides, a review and a discussion of the literature is carried out, with regard to the advantages of hypermedia in English Language Teaching. Following that, the selection of hypermedia material for implicit vocabulary teaching is prese...

  9. Biosignal controlled recommendation in entertainment systems

    NARCIS (Netherlands)

    Liu, H.

    2010-01-01

    With the explosive growth of the entertainment contents and the ubiquitous access of them via fixed or mobile computing devices, recommendation systems become essential tools to help the user to find the right entertainment at the right time and location. I envision that by integrating the bio

  10. Unilateral implicit motor learning deficit in developmental dyslexia.

    Science.gov (United States)

    Yang, Yang; Hong-Yan, Bi

    2011-02-01

    It has been suggested that developmental dyslexia involves various literacy, sensory, motor skill, and processing speed deficits. Some recent studies have shown that individuals with developmental dyslexia exhibit implicit motor learning deficits, which may be related to cerebellar functioning. However, previous studies on implicit motor learning in developmental dyslexics have produced conflicting results. Findings from cerebellar lesion patients have shown that patients' implicit motor learning performance varied when different hands were used to complete tasks. This suggests that dyslexia may have different effects on implicit motor learning between the two hands if cerebellar dysfunction is involved. To specify this question, we used a one-handed version of a serial reaction time task to compare the performance of 27 Chinese children with developmental dyslexics with another 27 age-matched children without reading difficulties. All the subjects were students from two primary schools, Grades 4 to 6. The results showed that children with developmental dyslexic responded more slowly than nondyslexic children, and exhibited no implicit motor learning in the condition of left-hand response. In contrast, there was no significant difference in reaction time between two groups of children when they used the right hand to respond. This finding indicates that children with developmental dyslexia exhibited normal motor skill and implicit motor learning ability provided the right hand was used. Taken together, these results suggested that Chinese children with developmental dyslexia exhibit unilateral deficits in motor skill and implicit motor learning in the left hand. Our findings lend partial support to the cerebellar deficit theory of developmental dyslexia.

  11. Implicit theories and ability emotional intelligence

    Science.gov (United States)

    Cabello, Rosario; Fernández-Berrocal, Pablo

    2015-01-01

    Previous research has shown that people differ in their implicit theories about the essential characteristics of intelligence and emotions. Some people believe these characteristics to be predetermined and immutable (entity theorists), whereas others believe that these characteristics can be changed through learning and behavior training (incremental theorists). The present study provides evidence that in healthy adults (N = 688), implicit beliefs about emotions and emotional intelligence (EI) may influence performance on the ability-based Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). Adults in our sample with incremental theories about emotions and EI scored higher on the MSCEIT than entity theorists, with implicit theories about EI showing a stronger relationship to scores than theories about emotions. Although our participants perceived both emotion and EI as malleable, they viewed emotions as more malleable than EI. Women and young adults in general were more likely to be incremental theorists than men and older adults. Furthermore, we found that emotion and EI theories mediated the relationship of gender and age with ability EI. Our findings suggest that people’s implicit theories about EI may influence their emotional abilities, which may have important consequences for personal and professional EI training. PMID:26052309

  12. Implicit theories and ability emotional intelligence

    Directory of Open Access Journals (Sweden)

    ROSARIO eCABELLO

    2015-05-01

    Full Text Available Previous research has shown that people differ in their implicit theories about the essential characteristics of intelligence and emotions. Some people believe these characteristics to be predetermined and immutable (entity theorists, whereas others believe that these characteristics can be changed through learning and behavior training (incremental theorists. The present study provides evidence that in healthy adults (N = 688, implicit beliefs about emotions and emotional intelligence (EI may influence performance on the ability-based Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT. Adults in our sample with incremental theories about emotions and EI scored higher on the MSCEIT than entity theorists, with implicit theories about EI showing a stronger relationship to scores than theories about emotions. Although our participants perceived both emotion and EI as malleable, they viewed emotions as more malleable than EI. Women and young adults in general were more likely to be incremental theorists than men and older adults. Furthermore, we found that emotion and EI theories mediated the relationship of gender and age with ability EI. Our findings suggest that people’s implicit theories about EI may influence their emotional abilities, which may have important consequences for personal and professional EI training.

  13. Implicit emotion regulation affects outcome evaluation.

    Science.gov (United States)

    Yang, Qiwei; Tang, Ping; Gu, Ruolei; Luo, Wenbo; Luo, Yue-jia

    2015-06-01

    Efficient implicit emotion regulation processes, which run without awareness, are important for human well-being. In this study, to investigate the influence of implicit emotion regulation on psychological and electrophysiological responses to gains and losses, participants were required to select between two Chinese four-character idioms to match the meaning of the third one before they performed a monetary gambling task. According to whether their meanings were related to emotion regulation, the idioms fell into two categories. Event-related potentials and self-rating emotional experiences to outcome feedback were recorded during the task. Priming emotion regulation reduced subjective emotional experience to both gains and losses and the amplitudes of the feedback-related negativity, while the P3 component was not influenced. According to these results, we suggest that the application of implicit emotion regulation effectively modulated the subjective emotional experience and the motivational salience of current outcomes without the cost of cognitive resources. This study implicates the potential significance of implicit emotion regulation in decision-making processes. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  14. Privacy-preserving recommender systems in dynamic environments

    NARCIS (Netherlands)

    Erkin, Z.; Veugen, T.; Lagendijk, R.L.

    2013-01-01

    Recommender systems play a crucial role today in on-line applications as they improve the customer satisfaction, and at the same time results in an increase in the profit for the service provider. However, there are serious privacy concerns as such systems rely on the personal data of the customers.

  15. Using the Implicit Association Test and the Implicit Relational Assessment Procedure to Measure Attitudes toward Meat and Vegetables in Vegetarians and Meat-Eaters

    Science.gov (United States)

    Barnes-Holmes, Dermot; Murtagh, Louise; Barnes-Holmes, Yvonne; Stewart, Ian

    2010-01-01

    The current study aimed to assess the implicit attitudes of vegetarians and non-vegetarians towards meat and vegetables, using the Implicit Association Test (IAT) and the Implicit Relational Assessment Procedure (IRAP). Both measures involved asking participants to respond, under time pressure, to pictures of meat or vegetables as either positive…

  16. Implicit computational complexity and compilers

    DEFF Research Database (Denmark)

    Rubiano, Thomas

    Complexity theory helps us predict and control resources, usually time and space, consumed by programs. Static analysis on specific syntactic criterion allows us to categorize some programs. A common approach is to observe the program’s data’s behavior. For instance, the detection of non...... evolution and a lot of research came from this theory. Until now, these implicit complexity theories were essentially applied on more or less toy languages. This thesis applies implicit computational complexity methods into “real life” programs by manipulating intermediate representation languages...

  17. Explicit goal-driven attention, unlike implicitly learned attention, spreads to secondary tasks.

    Science.gov (United States)

    Addleman, Douglas A; Tao, Jinyi; Remington, Roger W; Jiang, Yuhong V

    2018-03-01

    To what degree does spatial attention for one task spread to all stimuli in the attended region, regardless of task relevance? Most models imply that spatial attention acts through a unitary priority map in a task-general manner. We show that implicit learning, unlike endogenous spatial cuing, can bias spatial attention within one task without biasing attention to a spatially overlapping secondary task. Participants completed a visual search task superimposed on a background containing scenes, which they were told to encode for a later memory task. Experiments 1 and 2 used explicit instructions to bias spatial attention to one region for visual search; Experiment 3 used location probability cuing to implicitly bias spatial attention. In location probability cuing, a target appeared in one region more than others despite participants not being told of this. In all experiments, search performance was better in the cued region than in uncued regions. However, scene memory was better in the cued region only following endogenous guidance, not after implicit biasing of attention. These data support a dual-system view of top-down attention that dissociates goal-driven and implicitly learned attention. Goal-driven attention is task general, amplifying processing of a cued region across tasks, whereas implicit statistical learning is task-specific. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  18. Research on the Application of Persona in Book Recommendation System

    Science.gov (United States)

    Gao, Baozhong; Du, Shouyan; Li, Xinzhi; Liu, Fangai

    2017-10-01

    Currently, there still exists a host of problems in the book recommendation system, such as low accuracy, weak correlation and poor pertinence. Aiming to unravel these problems, this paper based on the theory of big data and data mining technology, through analyzing internet user behavior and the “5C” model of personal credit evaluation, combined with joint impact weight calculation method, which involves user grade, borrowing credit, book friend recommendation degree, book friend recommended adoption degree, borrowing frequency, borrowing number, and borrowing time interval. User activity and credit are also taken into account in the process of establishing user tagging system so as to build classified book recommendation service. This method is of universal meaning to the book recommendation service of smart campus with user as the core under big data environment.

  19. Alternating Direction Implicit (ADI) schemes for a PDE-based image osmosis model

    Science.gov (United States)

    Calatroni, L.; Estatico, C.; Garibaldi, N.; Parisotto, S.

    2017-10-01

    We consider Alternating Direction Implicit (ADI) splitting schemes to compute efficiently the numerical solution of the PDE osmosis model considered by Weickert et al. in [10] for several imaging applications. The discretised scheme is shown to preserve analogous properties to the continuous model. The dimensional splitting strategy traduces numerically into the solution of simple tridiagonal systems for which standard matrix factorisation techniques can be used to improve upon the performance of classical implicit methods, even for large time steps. Applications to the shadow removal problem are presented.

  20. Fully implicit 1D radiation hydrodynamics: Validation and verification

    International Nuclear Information System (INIS)

    Ghosh, Karabi; Menon, S.V.G.

    2010-01-01

    A fully implicit finite difference scheme has been developed to solve the hydrodynamic equations coupled with radiation transport. Solution of the time-dependent radiation transport equation is obtained using the discrete ordinates method and the energy flow into the Lagrangian meshes as a result of radiation interaction is fully accounted for. A tridiagonal matrix system is solved at each time step to determine the hydrodynamic variables implicitly. The results obtained from this fully implicit radiation hydrodynamics code in the planar geometry agrees well with the scaling law for radiation driven strong shock propagation in aluminium. For the point explosion problem the self similar solutions are compared with results for pure hydrodynamic case in spherical geometry. Results obtained when radiation interaction is also accounted agree with those of point explosion with heat conduction for lower input energies. Having, thus, benchmarked the code, self convergence of the method w.r.t. time step is studied in detail for both the planar and spherical problems. Spatial as well as temporal convergence rates are ≅1 as expected from the difference forms of mass, momentum and energy conservation equations. This shows that the asymptotic convergence rate of the code is realized properly.

  1. Not explicit but implicit memory is influenced by individual perception style

    OpenAIRE

    Hine, Kyoko; Tsushima, Yoshiaki

    2018-01-01

    Not only explicit but also implicit memory has considerable influence on our daily life. However, it is still unclear whether explicit and implicit memories are sensitive to individual differences. Here, we investigated how individual perception style (global or local) correlates with implicit and explicit memory. As a result, we found that not explicit but implicit memory was affected by the perception style: local perception style people more greatly used implicit memory than global percept...

  2. Implicit self-esteem compensation: automatic threat defense.

    Science.gov (United States)

    Rudman, Laurie A; Dohn, Matthew C; Fairchild, Kimberly

    2007-11-01

    Four experiments demonstrated implicit self-esteem compensation (ISEC) in response to threats involving gender identity (Experiment 1), implicit racism (Experiment 2), and social rejection (Experiments 3-4). Under conditions in which people might be expected to suffer a blow to self-worth, they instead showed high scores on 2 implicit self-esteem measures. There was no comparable effect on explicit self-esteem. However, ISEC was eliminated following self-affirmation (Experiment 3). Furthermore, threat manipulations increased automatic intergroup bias, but ISEC mediated these relationships (Experiments 2-3). Thus, a process that serves as damage control for the self may have negative social consequences. Finally, pretest anxiety mediated the relationship between threat and ISEC (Experiment 3), whereas ISEC negatively predicted anxiety among high-threat participants (Experiment 4), suggesting that ISEC may function to regulate anxiety. The implications of these findings for automatic emotion regulation, intergroup bias, and implicit self-esteem measures are discussed. (c) 2007 APA, all rights reserved.

  3. Convergence Analysis of Semi-Implicit Euler Methods for Solving Stochastic Age-Dependent Capital System with Variable Delays and Random Jump Magnitudes

    Directory of Open Access Journals (Sweden)

    Qinghui Du

    2014-01-01

    Full Text Available We consider semi-implicit Euler methods for stochastic age-dependent capital system with variable delays and random jump magnitudes, and investigate the convergence of the numerical approximation. It is proved that the numerical approximate solutions converge to the analytical solutions in the mean-square sense under given conditions.

  4. Health recommender systems: concepts, requirements, technical basics and challenges.

    Science.gov (United States)

    Wiesner, Martin; Pfeifer, Daniel

    2014-03-03

    During the last decades huge amounts of data have been collected in clinical databases representing patients' health states (e.g., as laboratory results, treatment plans, medical reports). Hence, digital information available for patient-oriented decision making has increased drastically but is often scattered across different sites. As as solution, personal health record systems (PHRS) are meant to centralize an individual's health data and to allow access for the owner as well as for authorized health professionals. Yet, expert-oriented language, complex interrelations of medical facts and information overload in general pose major obstacles for patients to understand their own record and to draw adequate conclusions. In this context, recommender systems may supply patients with additional laymen-friendly information helping to better comprehend their health status as represented by their record. However, such systems must be adapted to cope with the specific requirements in the health domain in order to deliver highly relevant information for patients. They are referred to as health recommender systems (HRS). In this article we give an introduction to health recommender systems and explain why they are a useful enhancement to PHR solutions. Basic concepts and scenarios are discussed and a first implementation is presented. In addition, we outline an evaluation approach for such a system, which is supported by medical experts. The construction of a test collection for case-related recommendations is described. Finally, challenges and open issues are discussed.

  5. Health Recommender Systems: Concepts, Requirements, Technical Basics and Challenges

    Directory of Open Access Journals (Sweden)

    Martin Wiesner

    2014-03-01

    Full Text Available During the last decades huge amounts of data have been collected in clinical databases representing patients’ health states (e.g., as laboratory results, treatment plans, medical reports. Hence, digital information available for patient-oriented decision making has increased drastically but is often scattered across different sites. As as solution, personal health record systems (PHRS are meant to centralize an individual’s health data and to allow access for the owner as well as for authorized health professionals. Yet, expert-oriented language, complex interrelations of medical facts and information overload in general pose major obstacles for patients to understand their own record and to draw adequate conclusions. In this context, recommender systems may supply patients with additional laymen-friendly information helping to better comprehend their health status as represented by their record. However, such systems must be adapted to cope with the specific requirements in the health domain in order to deliver highly relevant information for patients. They are referred to as health recommender systems (HRS. In this article we give an introduction to health recommender systems and explain why they are a useful enhancement to PHR solutions. Basic concepts and scenarios are discussed and a first implementation is presented. In addition, we outline an evaluation approach for such a system, which is supported by medical experts. The construction of a test collection for case-related recommendations is described. Finally, challenges and open issues are discussed.

  6. Coarse cluster enhancing collaborative recommendation for social network systems

    Science.gov (United States)

    Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng

    2017-10-01

    Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.

  7. Review of Recommender Systems Algorithms Utilized in Social Networks based e-Learning Systems & Neutrosophic System

    Directory of Open Access Journals (Sweden)

    A. A. Salama

    2015-03-01

    Full Text Available In this paper, we present a review of different recommender system algorithms that are utilized in social networks based e-Learning systems. Future research will include our proposed our e-Learning system that utilizes Recommender System and Social Network. Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache in [21, 22, 23] and Salama et al. in [24-66].The purpose of this paper is to utilize a neutrosophic set to analyze social networks data conducted through learning activities.

  8. Electronic Resources Management System: Recommendation Report 2017

    KAUST Repository

    Ramli, Rindra M.

    2017-05-01

    This recommendation report provides an overview of the selection process for the new Electronic Resources Management System. The library has decided to move away from Innovative Interfaces Millennium ERM module. The library reviewed 3 system as potential replacements namely: Proquest 360 Resource Manager, Ex Libris Alma and Open Source CORAL ERMS. After comparing and trialling the systems, it was decided to go for Proquest 360 Resource Manager.

  9. Chinese implicit leadership theory.

    Science.gov (United States)

    Ling, W; Chia, R C; Fang, L

    2000-12-01

    In a 1st attempt to identify an implicit theory of leadership among Chinese people, the authors developed the Chinese Implicit Leadership Scale (CILS) in Study 1. In Study 2, they administered the CILS to 622 Chinese participants from 5 occupation groups, to explore differences in perceptions of leadership. Factor analysis yielded 4 factors of leadership: Personal Morality, Goal Efficiency, Interpersonal Competence, and Versatility. Social groups differing in age, gender, education level, and occupation rated these factors. Results showed no significant gender differences, and the underlying cause for social group differences was education level. All groups gave the highest ratings to Interpersonal Competence, reflecting the enormous importance of this factor, which is consistent with Chinese collectivist values.

  10. Implicit and explicit interethnic attitudes and ethnic discrimination in hiring

    NARCIS (Netherlands)

    Blommaert, E.C.C.A.; Tubergen, F.A. van; Coenders, M.T.A.

    2012-01-01

    We study effects of explicit and implicit interethnic attitudes on ethnic discrimination in hiring. Unlike explicit attitudes, implicit attitudes are characterised by reduced controllability, awareness or intention. Effects of implicit interethnic attitudes on ethnic discrimination in the labour

  11. A Proposed Business Intelligent Framework for Recommender Systems

    Directory of Open Access Journals (Sweden)

    Sitalakshmi Venkatraman

    2017-11-01

    Full Text Available In this Internet age, recommender systems (RS have become popular, offering new opportunities and challenges to the business world. With a continuous increase in global competition, e-businesses, information portals, social networks and more, websites are required to become more user-centric and rely on the presence and role of RS in assisting users in better decision making. However, with continuous changes in user interests and consumer behavior patterns that are influenced by easy access to vast information and social factors, raising the quality of recommendations has become a challenge for recommender systems. There is a pressing need for exploring hybrid models of the five main types of RS, namely collaborative, demographic, utility, content and knowledge based approaches along with advancements in Big Data (BD to become more context-aware of the technology and social changes and to behave intelligently. There is a gap in literature with a research focus in this direction. This paper takes a step to address this by exploring a new paradigm of applying business intelligence (BI concepts to RS for intelligently responding to user changes and business complexities. A BI based framework adopting a hybrid methodology for RS is proposed with a focus on enhancing the RS performance. Such a business intelligent recommender system (BIRS can adopt On-line Analytical Processing (OLAP tools and performance monitoring metrics using data mining techniques of BI to enhance its own learning, user profiling and predictive models for making a more useful set of personalised recommendations to its users. The application of the proposed framework to a B2C e-commerce case example is presented.

  12. The Design and Implementation of an Intelligent Apparel Recommend Expert System

    Directory of Open Access Journals (Sweden)

    A. H. Dong

    2013-01-01

    Full Text Available Now with the rapid development of information science and technology, intelligent apparel recommend has drawn wide attention in apparel retail industry. Intelligent management and effective recommend are two issues of crucial importance for the retail store to enhance its corporate influence and increase its economic benefits. This paper proposes an intelligent recommend system design scheme for apparel retail which is based on expert system. By comprehensive utilization of database management and expert system technology, the proposed system provides a solid solution in improving the customer shopping experience. This paper presents a kind of object-oriented blackboard structure, which is applied in the apparel recommend expert system and establishes expert rule on the basis of apparel characteristic elements. Through the establishment of the rule base, the system generates personal recommend list by positive rule reasoning mechanism engine. The proposed method thus gives dress collocation scheme for the customer through the human-machine interaction from the point of view of the apparel experts. This design scheme avails the customers to experience targeted service with intellectualization, and personalization and it has certain reference significance for promoting apparel retail intelligence development.

  13. Which Recommender System Can Best Fit Social Learning Platforms?

    OpenAIRE

    Fazeli, Soude; Loni, Babak; Drachsler, Hendrik; Sloep, Peter

    2014-01-01

    In this presentation, we present a study that aims to develop a recommender system for social learning platforms that combine traditional learning management systems with commercial social networks like Facebook. We therefore take into account social interactions of users to make recommendations on learning resources. We propose to make use of graph-walking methods for improving performance of the well-known baseline algorithms. We evaluate the proposed graph-based approach in terms of their ...

  14. A Mobile Ecotourism Recommendations System Using Cars-Context Aware Approaches

    Directory of Open Access Journals (Sweden)

    Yani Nurhadryani

    2013-11-01

    Full Text Available The requirements to fullfill mobility of ecotourism activities have been urgent to support each traveler with the mobile gadget application. The objective of this research is to develop an application of recommendation system based on online user personalization. This application provided features to recommendation of ecotourism based on profile user and current location, then supplied information about distance and facilities in each ecotourism place. The main of computation worked online which was based on approach called as CARS (Context Aware Recommender Systems algorithm. The result showed that the application framework succeeded to give appropriate recommendations and explaination on a mobile platform both in the form of profile based spatial data and user preferences.

  15. A generic semi-implicit coupling methodology for use in RELAP5-3D(c)

    International Nuclear Information System (INIS)

    Weaver, W.L.; Tomlinson, E.T.; Aumiller, D.L.

    2002-01-01

    A generic semi-implicit coupling methodology has been developed and implemented in the RELAP5-3D (c) computer program. This methodology allows RELAP5-3D (c) to be used with other computer programs to perform integrated analyses of nuclear power reactor systems and related experimental facilities. The coupling methodology potentially allows different programs to be used to model different portions of the system. The programs are chosen based on their capability to model the phenomena that are important in the simulation in the various portions of the system being considered and may use different numbers of conservation equations to model fluid flow in their respective solution domains. The methodology was demonstrated using a test case in which the test geometry was divided into two parts, each of which was solved as a RELAP5-3D (c) simulation. This test problem exercised all of the semi-implicit coupling features that were implemented in RELAP5-3D (c) The results of this verification test case show that the semi-implicit coupling methodology produces the same answer as the simulation of the test system as a single process

  16. Implicit and Explicit Instruction of Spelling Rules

    Science.gov (United States)

    Kemper, M. J.; Verhoeven, L.; Bosman, A. M. T.

    2012-01-01

    The study aimed to compare the differential effectiveness of explicit and implicit instruction of two Dutch spelling rules. Students with and without spelling disabilities were instructed a spelling rule either implicitly or explicitly in two experiments. Effects were tested in a pretest-intervention-posttest control group design. Experiment 1…

  17. Content-based Music Search and Recommendation System

    Science.gov (United States)

    Takegawa, Kazuki; Hijikata, Yoshinori; Nishida, Shogo

    Recently, the turn volume of music data on the Internet has increased rapidly. This has increased the user's cost to find music data suiting their preference from such a large data set. We propose a content-based music search and recommendation system. This system has an interface for searching and finding music data and an interface for editing a user profile which is necessary for music recommendation. By exploiting the visualization of the feature space of music and the visualization of the user profile, the user can search music data and edit the user profile. Furthermore, by exploiting the infomation which can be acquired from each visualized object in a mutually complementary manner, we make it easier for the user to search music data and edit the user profile. Concretely, the system gives to the user an information obtained from the user profile when searching music data and an information obtained from the feature space of music when editing the user profile.

  18. Machine learning for recommendation systems in job postings selection

    OpenAIRE

    Marcos Santamarta, Victor

    2016-01-01

    Recommendation is a particular form of information filtering, that exploits past behaviors and user similarities to generate a list of information items that is personally tailored to an end-user?s preferences. Recommender systems have become extremely common in recent years, and are applied in a variety of applications. The most popular ones are probably movies, music, news, books, research articles, search queries, social tags, and products in general. However, there are also recommender sy...

  19. Implicit Motives, Explicit Traits, and Task and Contextual Performance at Work

    DEFF Research Database (Denmark)

    Lang, J.W.B.; Zettler, Ingo; Ewen, C.

    2012-01-01

    for implicit achievement). As a test of these theoretical ideas, we report a study in which employees (N = 241) filled out a questionnaire booklet and worked on an improved modern implicit motive measure, the operant motive test. Their supervisors rated their task and contextual performance. Results support 4...... apply these ideas in the context of industrial and organizational psychology and propose that 2 explicit traits work as channels for the expression of 3 core implicit motives in task and contextual job performance (extraversion for implicit affiliation and implicit power; explicit achievement...... of the 6 theoretical predictions and show that interactions between implicit motives and explicit traits increase the explained criterion variance in both task and contextual performance....

  20. Implicit Race/Ethnic Prejudice in Mexican Americans

    Science.gov (United States)

    Garza, Christelle Fabiola; Gasquoine, Philip Gerard

    2013-01-01

    Implicit race/ethnic prejudice was assessed using Spanish- and English-language versions of an Implicit Association Test that used Hispanic/Anglo first names and pleasant/unpleasant words as stimuli. This test was administered to a consecutive sample of Mexican American adults residing in the Rio Grande Valley region of Texas of whom about…

  1. Contexts in a Paper Recommendation System with Collaborative Filtering

    Science.gov (United States)

    Winoto, Pinata; Tang, Tiffany Ya; McCalla, Gordon

    2012-01-01

    Making personalized paper recommendations to users in an educational domain is not a trivial task of simply matching users' interests with a paper topic. Therefore, we proposed a context-aware multidimensional paper recommendation system that considers additional user and paper features. Earlier experiments on experienced graduate students…

  2. Solving Kepler's equation using implicit functions

    Science.gov (United States)

    Mortari, Daniele; Elipe, Antonio

    2014-01-01

    A new approach to solve Kepler's equation based on the use of implicit functions is proposed here. First, new upper and lower bounds are derived for two ranges of mean anomaly. These upper and lower bounds initialize a two-step procedure involving the solution of two implicit functions. These two implicit functions, which are non-rational (polynomial) Bézier functions, can be linear or quadratic, depending on the derivatives of the initial bound values. These are new initial bounds that have been compared and proven more accurate than Serafin's bounds. The procedure reaches machine error accuracy with no more that one quadratic and one linear iterations, experienced in the "tough range", where the eccentricity is close to one and the mean anomaly to zero. The proposed method is particularly suitable for space-based applications with limited computational capability.

  3. Implicit attitudes towards homosexuality: reliability, validity, and controllability of the IAT.

    Science.gov (United States)

    Banse, R; Seise, J; Zerbes, N

    2001-01-01

    Two experiments were conducted to investigate the psychometric properties of an Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) that was adapted to measure implicit attitudes towards homosexuality. In a first experiment, the validity of the Homosexuality-IAT was tested using a known group approach. Implicit and explicit attitudes were assessed in heterosexual and homosexual men and women (N = 101). The results provided compelling evidence for the convergent and discriminant validity of the Homosexuality-IAT as a measure of implicit attitudes. No evidence was found for two alternative explanations of IAT effects (familiarity with stimulus material and stereotype knowledge). The internal consistency of IAT scores was satisfactory (alpha s > .80), but retest correlations were lower. In a second experiment (N = 79) it was shown that uninformed participants were able to fake positive explicit but not implicit attitudes. Discrepancies between implicit and explicit attitudes towards homosexuality could be partially accounted for by individual differences in the motivation to control prejudiced behavior, thus providing independent evidence for the validity of the implicit attitude measure. Neither explicit nor implicit attitudes could be changed by persuasive messages. The results of both experiments are interpreted as evidence for a single construct account of implicit and explicit attitudes towards homosexuality.

  4. Group Recommendation Systems Based on External Social-Trust Networks

    Directory of Open Access Journals (Sweden)

    Guang Fang

    2018-01-01

    Full Text Available With the development of social networks and online mobile communities, group recommendation systems support users’ interaction with similar interests or purposes with others. We often provide some advices to the close friends, such as listening to favorite music and sharing favorite dishes. However, users’ personalities have been ignored by the traditional group recommendation systems while the majority is satisfied. In this paper, a method of group recommendation based on external social-trust networks is proposed, which builds a group profile by analyzing not only users’ preferences, but also the social relationships between members inside and outside of the group. We employ the users’ degree of disagreement to adjust group preference rating by external information of social-trust network. Moreover, having a discussion about different social network utilization ratio, we proposed a method to work for smaller group size. The experimental results show that the proposed method has consistently higher precision and leads to satisfactory recommendations for groups.

  5. Implicit bias and its relation to health disparities: a teaching program and survey of medical students.

    Science.gov (United States)

    Gonzalez, Cristina M; Kim, Mimi Y; Marantz, Paul R

    2014-01-01

    The varying treatment of different patients by the same physician are referred to as within provider disparities. These differences can contribute to health disparities and are thought to be the result of implicit bias due to unintentional, unconscious assumptions. The purpose is to describe an educational intervention addressing both health disparities and physician implicit bias and the results of a subsequent survey exploring medical students' attitudes and beliefs toward subconscious bias and health disparities. A single session within a larger required course was devoted to health disparities and the physician's potential to contribute to health disparities through implicit bias. Following the session the students were anonymously surveyed on their Implicit Association Test (IAT) results, their attitudes and experiences regarding the fairness of the health care system, and the potential impact of their own implicit bias. The students were categorized based on whether they disagreed ("deniers") or agreed ("accepters") with the statement "Unconscious bias might affect some of my clinical decisions or behaviors." Data analysis focused specifically on factors associated with this perspective. The survey response rate was at least 69%. Of the responders, 22% were "deniers" and 77% were "accepters." Demographics between the two groups were not significantly different. Deniers were significantly more likely than accepters to report IAT results with implicit preferences toward self, to believe the IAT is invalid, and to believe that doctors and the health system provide equal care to all and were less likely to report having directly observed inequitable care. The recognition of bias cannot be taught in a single session. Our experience supports the value of teaching medical students to recognize their own implicit biases and develop skills to overcome them in each patient encounter, and in making this instruction part of the compulsory, longitudinal undergraduate

  6. Gambling and Sport: Implicit Association and Explicit Intention Among Underage Youth.

    Science.gov (United States)

    Li, En; Langham, Erika; Browne, Matthew; Rockloff, Matthew; Thorne, Hannah

    2018-03-23

    This study examined whether an implicit association existed between gambling and sport among underage youth in Australia, and whether this implicit association could shape their explicit intention to gamble. A sample of 14-17 year old Australian participants completed two phases of tasks, including an implicit association test based online experiment, and a post-experiment online survey. The results supported the existence of an implicit association between gambling and sport among the participants. This implicit association became stronger when they saw sport-relevant (vs. sport-irrelevant) gambling logos, or gambling-relevant (vs. gambling-irrelevant) sport names. In addition, this implicit association was positively related to the amount of sport viewing, but only among those participants who had more favorable gambling attitudes. Lastly, gambling attitudes and advertising knowledge, rather than the implicit association, turned out to be significant predictors of the explicit intention to gamble.

  7. Toward textbook multigrid efficiency for fully implicit resistive magnetohydrodynamics

    International Nuclear Information System (INIS)

    Adams, Mark F.; Samtaney, Ravi; Brandt, Achi

    2010-01-01

    Multigrid methods can solve some classes of elliptic and parabolic equations to accuracy below the truncation error with a work-cost equivalent to a few residual calculations - so-called 'textbook' multigrid efficiency. We investigate methods to solve the system of equations that arise in time dependent magnetohydrodynamics (MHD) simulations with textbook multigrid efficiency. We apply multigrid techniques such as geometric interpolation, full approximate storage, Gauss-Seidel smoothers, and defect correction for fully implicit, nonlinear, second-order finite volume discretizations of MHD. We apply these methods to a standard resistive MHD benchmark problem, the GEM reconnection problem, and add a strong magnetic guide field, which is a critical characteristic of magnetically confined fusion plasmas. We show that our multigrid methods can achieve near textbook efficiency on fully implicit resistive MHD simulations.

  8. Toward textbook multigrid efficiency for fully implicit resistive magnetohydrodynamics

    International Nuclear Information System (INIS)

    Adams, Mark F.; Samtaney, Ravi; Brandt, Achi

    2013-01-01

    Multigrid methods can solve some classes of elliptic and parabolic equations to accuracy below the truncation error with a work-cost equivalent to a few residual calculations so-called textbook multigrid efficiency. We investigate methods to solve the system of equations that arise in time dependent magnetohydrodynamics (MHD) simulations with textbook multigrid efficiency. We apply multigrid techniques such as geometric interpolation, full approximate storage, Gauss-Seidel smoothers, and defect correction for fully implicit, nonlinear, second-order finite volume discretizations of MHD. We apply these methods to a standard resistive MHD benchmark problem, the GEM reconnection problem, and add a strong magnetic guide field, which is a critical characteristic of magnetically confined fusion plasmas. We show that our multigrid methods can achieve near textbook efficiency on fully implicit resistive MHD simulations.

  9. Implicit but not explicit self-esteem predicts future depressive symptomatology.

    Science.gov (United States)

    Franck, Erik; De Raedt, Rudi; De Houwer, Jan

    2007-10-01

    To date, research on the predictive validity of implicit self-esteem for depressive relapse is very sparse. In the present study, we assessed implicit self-esteem using the Name Letter Preference Task and explicit self-esteem using the Rosenberg self-esteem scale in a group of currently depressed patients, formerly depressed individuals, and never depressed controls. In addition, we examined the predictive validity of explicit, implicit, and the interaction of explicit and implicit self-esteem in predicting future symptoms of depression in formerly depressed individuals and never depressed controls. The results showed that currently depressed individuals reported a lower explicit self-esteem as compared to formerly depressed individuals and never depressed controls. In line with previous research, all groups showed a positive implicit self-esteem not different from each other. Furthermore, after controlling for initial depressive symptomatology, implicit but not explicit self-esteem significantly predicted depressive symptoms at six months follow-up. Although implicit self-esteem assessed with the Name Letter Preference Test was not different between formerly depressed individuals and never depressed controls, the findings suggest it is an interesting variable in the study of vulnerability for depression relapse.

  10. Ego Depletion Impairs Implicit Learning

    Science.gov (United States)

    Thompson, Kelsey R.; Sanchez, Daniel J.; Wesley, Abigail H.; Reber, Paul J.

    2014-01-01

    Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent. PMID:25275517

  11. Ego depletion impairs implicit learning.

    Directory of Open Access Journals (Sweden)

    Kelsey R Thompson

    Full Text Available Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent.

  12. Ego depletion impairs implicit learning.

    Science.gov (United States)

    Thompson, Kelsey R; Sanchez, Daniel J; Wesley, Abigail H; Reber, Paul J

    2014-01-01

    Implicit skill learning occurs incidentally and without conscious awareness of what is learned. However, the rate and effectiveness of learning may still be affected by decreased availability of central processing resources. Dual-task experiments have generally found impairments in implicit learning, however, these studies have also shown that certain characteristics of the secondary task (e.g., timing) can complicate the interpretation of these results. To avoid this problem, the current experiments used a novel method to impose resource constraints prior to engaging in skill learning. Ego depletion theory states that humans possess a limited store of cognitive resources that, when depleted, results in deficits in self-regulation and cognitive control. In a first experiment, we used a standard ego depletion manipulation prior to performance of the Serial Interception Sequence Learning (SISL) task. Depleted participants exhibited poorer test performance than did non-depleted controls, indicating that reducing available executive resources may adversely affect implicit sequence learning, expression of sequence knowledge, or both. In a second experiment, depletion was administered either prior to or after training. Participants who reported higher levels of depletion before or after training again showed less sequence-specific knowledge on the post-training assessment. However, the results did not allow for clear separation of ego depletion effects on learning versus subsequent sequence-specific performance. These results indicate that performance on an implicitly learned sequence can be impaired by a reduction in executive resources, in spite of learning taking place outside of awareness and without conscious intent.

  13. PRS: PERSONNEL RECOMMENDATION SYSTEM FOR HUGE DATA ANALYSIS USING PORTER STEMMER

    OpenAIRE

    T N Chiranjeevi; R H Vishwanath

    2016-01-01

    Personal recommendation system is one which gives better and preferential recommendation to the users to satisfy their personalized requirements such as practical applications like Webpage Preferences, Sport Videos preferences, Stock selection based on price, TV preferences, Hotel preferences, books, Mobile phones, CDs and various other products now use recommender systems. The existing Pearson Correlation Coefficient (PCC) and item-based algorithm using PCC, are called as UPCC and IPCC respe...

  14. Implicit Measures: A Normative Analysis and Review

    Science.gov (United States)

    De Houwer, Jan; Teige-Mocigemba, Sarah; Spruyt, Adriaan; Moors, Agnes

    2009-01-01

    Implicit measures can be defined as outcomes of measurement procedures that are caused in an automatic manner by psychological attributes. To establish that a measurement outcome is an implicit measure, one should examine (a) whether the outcome is causally produced by the psychological attribute it was designed to measure, (b) the nature of the…

  15. Explicit versus Implicit Stereotypes: "What Biases Do I Really Hold?"

    Science.gov (United States)

    Morgan, Melanie

    2008-01-01

    This article presents an activity in which students explore the impact of implicit stereotypes in everyday interactions while examining issues of attitudinal measurement. Social cognitions that underlie stereotypes often operate implicitly and even unconsciously. Consequently, these implicit attitudes have the potential to affect the way people…

  16. Using Recommendation System for E-learning Environments at degree level

    Directory of Open Access Journals (Sweden)

    Rubén González Crespo

    2009-12-01

    Full Text Available Nowadays, new technologies and the fast growth of the Internet have made access to information easier for all kind of people, raising new challenges to education when using Internet as a medium. One of the best examples is how to guide students in their learning processes.The need to look for guidance from their teachers or other companions that many Internet users experience when endeavoring to choose their readings, exercises o practices is a very common reality. In order to cater for this need many different information and recommendation strategies have been developed. Recommendation Systems is one of these.Recommendation Systems try to help the user, presenting him those objects he could be more interested in, based on his known preferences or on those of other users with similar characteristics.This document tries to present the current situation with regards to Recommendation Systems and their application on distance education over the Internet.

  17. Implicit Learning of Recursive Context-Free Grammars

    Science.gov (United States)

    Rohrmeier, Martin; Fu, Qiufang; Dienes, Zoltan

    2012-01-01

    Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning. PMID:23094021

  18. Implicit learning of recursive context-free grammars.

    Science.gov (United States)

    Rohrmeier, Martin; Fu, Qiufang; Dienes, Zoltan

    2012-01-01

    Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning.

  19. Implicit Recognition Based on Lateralized Perceptual Fluency

    Directory of Open Access Journals (Sweden)

    Iliana M. Vargas

    2012-02-01

    Full Text Available In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this “implicit recognition” results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

  20. Implicit learning of recursive context-free grammars.

    Directory of Open Access Journals (Sweden)

    Martin Rohrmeier

    Full Text Available Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams between individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex context-free structures, which model some features of natural languages. They support the relevance of artificial grammar learning for probing mechanisms of language learning and challenge existing theories and computational models of implicit learning.

  1. Implicit recognition based on lateralized perceptual fluency.

    Science.gov (United States)

    Vargas, Iliana M; Voss, Joel L; Paller, Ken A

    2012-02-06

    In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this "implicit recognition" results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

  2. Vote Stuffing Control in IPTV-based Recommender Systems

    Science.gov (United States)

    Bhatt, Rajen

    Vote stuffing is a general problem in the functioning of the content rating-based recommender systems. Currently IPTV viewers browse various contents based on the program ratings. In this paper, we propose a fuzzy clustering-based approach to remove the effects of vote stuffing and consider only the genuine ratings for the programs over multiple genres. The approach requires only one authentic rating, which is generally available from recommendation system administrators or program broadcasters. The entire process is automated using fuzzy c-means clustering. Computational experiments performed over one real-world program rating database shows that the proposed approach is very efficient for controlling vote stuffing.

  3. PRUB: A Privacy Protection Friend Recommendation System Based on User Behavior

    Directory of Open Access Journals (Sweden)

    Wei Jiang

    2016-01-01

    Full Text Available The fast developing social network is a double-edged sword. It remains a serious problem to provide users with excellent mobile social network services as well as protecting privacy data. Most popular social applications utilize behavior of users to build connection with people having similar behavior, thus improving user experience. However, many users do not want to share their certain behavioral information to the recommendation system. In this paper, we aim to design a secure friend recommendation system based on the user behavior, called PRUB. The system proposed aims at achieving fine-grained recommendation to friends who share some same characteristics without exposing the actual user behavior. We utilized the anonymous data from a Chinese ISP, which records the user browsing behavior, for 3 months to test our system. The experiment result shows that our system can achieve a remarkable recommendation goal and, at the same time, protect the privacy of the user behavior information.

  4. Not explicit but implicit memory is influenced by individual perception style.

    Science.gov (United States)

    Hine, Kyoko; Tsushima, Yoshiaki

    2018-01-01

    Not only explicit but also implicit memory has considerable influence on our daily life. However, it is still unclear whether explicit and implicit memories are sensitive to individual differences. Here, we investigated how individual perception style (global or local) correlates with implicit and explicit memory. As a result, we found that not explicit but implicit memory was affected by the perception style: local perception style people more greatly used implicit memory than global perception style people. These results help us to make the new effective application adapting to individual perception style and understand some clinical symptoms such as autistic spectrum disorder. Furthermore, this finding might give us new insight of memory involving consciousness and unconsciousness as well as relationship between implicit/explicit memory and individual perception style.

  5. Hierarchically Structured Recommender System for Improving NPS

    Science.gov (United States)

    Kuang, Jieyan

    2016-01-01

    Net Promoter System (NPS) is well known as an evaluation measure of the growth engine of big companies in the business area. The ultimate goal of my research is to build an action rules and meta-actions based recommender system for improving NPS scores of 34 companies (clients) dealing with similar businesses in the US and Canada. With the given…

  6. Are implicit self-esteem measures valid for assessing individual and cultural differences?

    Science.gov (United States)

    Falk, Carl F; Heine, Steven J; Takemura, Kosuke; Zhang, Cathy X J; Hsu, Chih-Wei

    2015-02-01

    Our research utilized two popular theoretical conceptualizations of implicit self-esteem: 1) implicit self-esteem as a global automatic reaction to the self; and 2) implicit self-esteem as a context/domain specific construct. Under this framework, we present an extensive search for implicit self-esteem measure validity among different cultural groups (Study 1) and under several experimental manipulations (Study 2). In Study 1, Euro-Canadians (N = 107), Asian-Canadians (N = 187), and Japanese (N = 112) completed a battery of implicit self-esteem, explicit self-esteem, and criterion measures. Included implicit self-esteem measures were either popular or provided methodological improvements upon older methods. Criterion measures were sampled from previous research on implicit self-esteem and included self-report and independent ratings. In Study 2, Americans (N = 582) completed a shorter battery of these same types of measures under either a control condition, an explicit prime meant to activate the self-concept in a particular context, or prime meant to activate self-competence related implicit attitudes. Across both studies, explicit self-esteem measures far outperformed implicit self-esteem measures in all cultural groups and under all experimental manipulations. Implicit self-esteem measures are not valid for individual or cross-cultural comparisons. We speculate that individuals may not form implicit associations with the self as an attitudinal object. © 2013 Wiley Periodicals, Inc.

  7. Chinese Undergraduates' Explicit and Implicit Attitudes toward Persons with Disabilities

    Science.gov (United States)

    Chen, Shuang; Ma, Li; Zhang, Jian-Xin

    2011-01-01

    The present study is aimed at examining implicit and explicit attitudes toward persons with disabilities among Chinese college students. The "Implicit Association Test" was used to measure their implicit attitudes, whereas their explicit attitudes toward persons with disabilities were measured by using a scale of three items.…

  8. Self-Regulation and Implicit Attitudes Toward Physical Activity Influence Exercise Behavior.

    Science.gov (United States)

    Padin, Avelina C; Emery, Charles F; Vasey, Michael; Kiecolt-Glaser, Janice K

    2017-08-01

    Dual-process models of health behavior posit that implicit and explicit attitudes independently drive healthy behaviors. Prior evidence indicates that implicit attitudes may be related to weekly physical activity (PA) levels, but the extent to which self-regulation attenuates this link remains unknown. This study examined the associations between implicit attitudes and self-reported PA during leisure time among 150 highly active young adults and evaluated the extent to which effortful control (one aspect of self-regulation) moderated this relationship. Results indicated that implicit attitudes toward exercise were unrelated to average workout length among individuals with higher effortful control. However, those with lower effortful control and more negative implicit attitudes reported shorter average exercise sessions compared with those with more positive attitudes. Implicit and explicit attitudes were unrelated to total weekly PA. A combination of poorer self-regulation and negative implicit attitudes may leave individuals vulnerable to mental and physical health consequences of low PA.

  9. Independent operation of implicit working memory under cognitive load.

    Science.gov (United States)

    Ji, Eunhee; Lee, Kyung Min; Kim, Min-Shik

    2017-10-01

    Implicit working memory (WM) has been known to operate non-consciously and unintentionally. The current study investigated whether implicit WM is a discrete mechanism from explicit WM in terms of cognitive resource. To induce cognitive resource competition, we used a conjunction search task (Experiment 1) and imposed spatial WM load (Experiment 2a and 2b). Each trial was composed of a set of five consecutive search displays. The location of the first four displays appeared as per pre-determined patterns, but the fifth display could follow the same pattern or not. If implicit WM can extract the moving pattern of stimuli, response times for the fifth target would be faster when it followed the pattern compared to when it did not. Our results showed implicit WM can operate when participants are searching for the conjunction target and even while maintaining spatial WM information. These results suggest that implicit WM is independent from explicit spatial WM. Copyright © 2017. Published by Elsevier Inc.

  10. Interest Aware Location-Based Recommender System Using Geo-Tagged Social Media

    Directory of Open Access Journals (Sweden)

    Basma AlBanna

    2016-12-01

    Full Text Available Advances in location acquisition and mobile technologies led to the addition of the location dimension to Social Networks (SNs and to the emergence of a newer class called Location-Based Social Networks (LBSNs. While LBSNs are richer in their model and functions than SNs, they fail so far to attract as many users as SNs. On the other hand, SNs have large amounts of geo-tagged media that are under-utilized. In this paper, we propose an Interest-Aware Location-Based Recommender system (IALBR, which combines the advantages of both LBSNs and SNs, in order to provide interest-aware location-based recommendations. This recommender system is proposed as an extension to LBSNs. It is novel in: (1 utilizing the geo-content in both LBSNs and SNs; (2 ranking the recommendations based on a novel scoring method that maps to the user interests. It also works for passive users who are not active content contributors to the LBSN. This feature is critical to increase the number of LBSN users. Moreover, it helps with reducing the cold start problem, which is a common problem facing the new users of recommender systems who get random unsatisfying recommendations. This is due to the lack of user interest awareness, which is reliant on user history in most of the recommenders. We evaluated our system with a large-scale real dataset collected from foursquare with respect to precision, recall and the f-measure. We also compared the results with a ground truth system using metrics like the normalized discounted cumulative gain and the mean absolute error. The results confirm that the proposed IALBR generates more efficient recommendations than baselines in terms of interest awareness.

  11. A Decision Fusion Framework for Treatment Recommendation Systems.

    Science.gov (United States)

    Mei, Jing; Liu, Haifeng; Li, Xiang; Xie, Guotong; Yu, Yiqin

    2015-01-01

    Treatment recommendation is a nontrivial task--it requires not only domain knowledge from evidence-based medicine, but also data insights from descriptive, predictive and prescriptive analysis. A single treatment recommendation system is usually trained or modeled with a limited (size or quality) source. This paper proposes a decision fusion framework, combining both knowledge-driven and data-driven decision engines for treatment recommendation. End users (e.g. using the clinician workstation or mobile apps) could have a comprehensive view of various engines' opinions, as well as the final decision after fusion. For implementation, we leverage several well-known fusion algorithms, such as decision templates and meta classifiers (of logistic and SVM, etc.). Using an outcome-driven evaluation metric, we compare the fusion engine with base engines, and our experimental results show that decision fusion is a promising way towards a more valuable treatment recommendation.

  12. Implicit Self-Esteem in Borderline Personality and Depersonalization Disorder

    OpenAIRE

    Hedrick, Alexis N.; Berlin, Heather A.

    2012-01-01

    Self-identity is disrupted in people with borderline personality disorder (BPD) and depersonalization disorder (DPD), fluctuating with sudden shifts in affect in BPD and experienced as detached in DPD. Measures of implicit self-esteem, free from conscious control and presentation biases, may highlight how such disruptions of self-concept differentially affect these two populations on an unconscious level. We examined implicit self-esteem using the Implicit Association Test, along with measure...

  13. Multimedia services in intelligent environments advances in recommender systems

    CERN Document Server

    Virvou, Maria; Jain, Lakhmi

    2013-01-01

    Multimedia services are now commonly used in various activities in the daily lives of humans. Related application areas include services that allow access to large depositories of information, digital libraries, e-learning and e-education, e-government and e-governance, e-commerce and e-auctions, e-entertainment, e-health and e-medicine, and e-legal services, as well as their mobile counterparts (i.e., m-services). Despite the tremendous growth of multimedia services over the recent years, there is an increasing demand for their further development. This demand is driven by the ever-increasing desire of society for easy accessibility to information in friendly, personalized and adaptive environments. In this book at hand, we examine recent Advances in Recommender Systems. Recommender systems are crucial in multimedia services, as they aim at protecting the service users from information overload. The book includes nine chapters, which present various recent research results in recommender systems. This resear...

  14. Dissociation between implicit and explicit expectancies of cannabis use in adolescence.

    Science.gov (United States)

    Schmits, Emilie; Maurage, Pierre; Thirion, Romain; Quertemont, Etienne

    2015-12-30

    Cannabis is one of the most commonly drugs used by teenagers. Expectancies about its effects play a crucial role in cannabis consumption. Various tools have been used to assess expectancies, mainly self-report questionnaires measuring explicit expectancies, but implicit measures based on experimental tasks have also been developed, measuring implicit expectancies. The aim of this study was to simultaneously assess implicit/explicit expectancies related to cannabis among adolescent users and non-users. 130 teenagers attending school (55 girls) were enrolled (Age: M=16.40 years); 43.84% had never used cannabis ("non-users") and 56.16% had used cannabis ("users"). They completed self-report questionnaires evaluating cannabis use, cannabis-related problems, effect expectancies (explicit expectancies), alcohol use, social and trait anxiety, depression, as well as three Implicit Association Tests (IAT) assessing implicit expectancies. Adolescents manifested more implicit affective associations (relaxation, excitation, negative) than neutral ones regarding cannabis. These were not related to explicit expectancies. Cannabis users reported more implicit relaxation expectancies and less negative explicit expectancies than non-users. The frequency of use and related problems were positively associated with the explicit expectancies regarding relaxation and enhancement, and were negatively associated with negative explicit expectancies and negative implicit expectancies. Findings indicate that implicit and explicit expectancies play different roles in cannabis use by adolescents. The implications for experimentation and prevention are discussed. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  15. Implicit Structured Sequence Learning: An FMRI Study of the Structural Mere-Exposure Effect

    Directory of Open Access Journals (Sweden)

    Vasiliki eFolia

    2014-02-01

    Full Text Available In this event-related FMRI study we investigated the effect of five days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the FMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45 and the medial prefrontal regions (centered on BA 8/32. Importantly, and central to this study, the inclusion of a naive preference FMRI baseline measurement allowed us to conclude that these FMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax in unsupervised AGL paradigms with proper learning designs.

  16. A method for predicting errors when interacting with finite state systems. How implicit learning shapes the user's knowledge of a system

    International Nuclear Information System (INIS)

    Javaux, Denis

    2002-01-01

    This paper describes a method for predicting the errors that may appear when human operators or users interact with systems behaving as finite state systems. The method is a generalization of a method used for predicting errors when interacting with autopilot modes on modern, highly computerized airliners [Proc 17th Digital Avionics Sys Conf (DASC) (1998); Proc 10th Int Symp Aviat Psychol (1999)]. A cognitive model based on spreading activation networks is used for predicting the user's model of the system and its impact on the production of errors. The model strongly posits the importance of implicit learning in user-system interaction and its possible detrimental influence on users' knowledge of the system. An experiment conducted with Airbus Industrie and a major European airline on pilots' knowledge of autopilot behavior on the A340-200/300 confirms the model predictions, and in particular the impact of the frequencies with which specific state transitions and contexts are experienced

  17. Implicit mentalizing persists beyond early childhood and is profoundly impaired in children with autism spectrum conditions

    Directory of Open Access Journals (Sweden)

    Tobias Schuwerk

    2016-10-01

    Full Text Available Implicit mentalizing, a fast, unconscious and rigid way of processing other's mental states has recently received much interest in typical social cognitive development in early childhood and in adults with autism spectrum conditions (ASC. This research suggests that already infants implicitly mentalize, and that adults with ASC have a sustained implicit mentalizing deficit. Yet, we have only sparse empirical evidence on implicit mentalizing beyond early childhood, and deviations thereof in children with ASC. Here, we administered an implicit mentalizing eye tracking task to assess the sensitivity to false beliefs to a group of 8-year-old children with and without ASC, matched for chronological age, verbal and nonverbal IQ. As previous research suggested that presenting outcomes of belief-based actions leads to fast learning from experience and false belief-congruent looking behavior in adults with ASC, we were also interested in whether already children with ASC learn from such information. Our results provide support for a persistent implicit mentalizing ability in neurotypical development beyond early childhood. Further, they confirmed an implicit mentalizing deficit in children with ASC, even when they are closely matched to controls for explicit mentalizing skills. In contrast to previous findings with adults, no experience-based modulation of anticipatory looking was observed. It seems that children with ASC have not yet developed compensatory general purpose learning mechanisms. The observed intact explicit, but impaired implicit mentalizing in ASC, and correlation patterns between mentalizing tasks and executive function tasks, are in line with theories on two dissociable mentalizing systems.

  18. Implicit and explicit memory in survivors of chronic interpersonal violence.

    Science.gov (United States)

    Minshew, Reese; D'Andrea, Wendy

    2015-01-01

    We investigated the relationship of implicit and explicit memory to a range of symptoms in a sample of 27 women with exposure to chronic interpersonal violence (IPV). Participants viewed the first 3 letters ("stems") of trauma-related, general threat, and neutral words; valenced words were matched with neutral words with the same stem. Free recall and a word-stem completion task were used to test explicit and implicit memory, respectively. Participants exhibited increased implicit memory for trauma-related words as compared with both general threat words and neutral "match" words. They also showed increased explicit memory for both general threat and trauma-related words. Finally, although neither implicit nor explicit memory was correlated with PTSD symptoms, implicit memory for trauma-related words was significantly correlated with symptoms associated with ongoing IPV. Interpersonal sensitivity, hostility, and alexithymia were significantly correlated with implicit, but not explicit, memory for trauma words. Somatization, dissociation, and alexithymia were negatively correlated with explicit, but not implicit, memory for general-threat words. These findings suggest that memory processes in survivors of IPV are closely related to the symptom profile associated with complex trauma. Exploring memory processes in survivors of IPV may lend unique insight into the development and maintenance of the symptom profile associated with IPV. (c) 2015 APA, all rights reserved).

  19. Implicit and explicit memory for spatial information in Alzheimer's disease.

    Science.gov (United States)

    Kessels, R P C; Feijen, J; Postma, A

    2005-01-01

    There is abundant evidence that memory impairment in dementia in patients with Alzheimer's disease (AD) is related to explicit, conscious forms of memory, whereas implicit, unconscious forms of memory function remain relatively intact or are less severely affected. Only a few studies have been performed on spatial memory function in AD, showing that AD patients' explicit spatial memory is impaired, possibly related to hippocampal dysfunction. However, studies on implicit spatial memory in AD are lacking. The current study set out to investigate implicit and explicit spatial memory in AD patients (n=18) using an ecologically valid computer task, in which participants had to remember the locations of various objects in common rooms. The contribution of implicit and explicit memory functions was estimated by means of the process dissociation procedure. The results show that explicit spatial memory is impaired in AD patients compared with a control group (n=21). However, no group difference was found on implicit spatial function. This indicates that spared implicit memory in AD extends to the spatial domain, while the explicit spatial memory function deteriorates. Clinically, this finding might be relevant, in that an intact implicit memory function might be helpful in overcoming problems in explicit processing. Copyright (c) 2005 S. Karger AG, Basel.

  20. Components of implicit stigma against mental illness among Chinese students.

    Directory of Open Access Journals (Sweden)

    Xiaogang Wang

    Full Text Available Although some research has examined negative automatic aspects of attitudes toward mental illness via relatively indirect measures among Western samples, it is unclear whether negative attitudes can be automatically activated in individuals from non-Western countries. This study attempted to validate results from Western samples with Chinese college students. We first examined the three-component model of implicit stigma (negative cognition, negative affect, and discriminatory tendencies toward mental illness with the Single Category Implicit Association Test (SC-IAT. We also explored the relationship between explicit and implicit stigma among 56 Chinese university college students. In the three separate SC-IATs and the combined SC-IAT, automatic associations between mental illness and negative descriptors were stronger relative to those with positive descriptors and the implicit effect of cognitive and affective SC-IATs were significant. Explicit and implicit measures of stigma toward mental illness were unrelated. In our sample, women's overall attitudes toward mental illness were more negative than men's were, but no gender differences were found for explicit measures. These findings suggested that implicit stigma toward mental illness exists in Chinese students, and provide some support for the three-component model of implicit stigma toward mental illness. Future studies that focus on automatic components of stigmatization and stigma-reduction in China are warranted.

  1. Implicit Beliefs about Ideal Body Image Predict Body Image Dissatisfaction

    Directory of Open Access Journals (Sweden)

    Niclas eHeider

    2015-10-01

    Full Text Available We examined whether implicit measures of actual and ideal body image can be used to predict body dissatisfaction in young female adults. Participants completed two Implicit Relational Assessment Procedures (IRAPs to examine their implicit beliefs concerning actual (e.g., I am thin and desired ideal body image (e.g., I want to be thin. Body dissatisfaction was examined via self-report questionnaires and rating scales. As expected, differences in body dissatisfaction exerted a differential influence on the two IRAP scores. Specifically, the implicit belief that one is thin was lower in participants who exhibited a high degree of body dissatisfaction than in participants who exhibited a low degree of body dissatisfaction. In contrast, the implicit desire to be thin (i.e., thin ideal body image was stronger in participants who exhibited a high level of body dissatisfaction than in participants who were less dissatisfied with their body. Adding further weight to the idea that both IRAP measures captured different underlying constructs, we also observed that they correlated differently with body mass index, explicit body dissatisfaction, and explicit measures of actual and ideal body image. More generally, these findings underscore the advantage of using implicit measures that incorporate relational information relative to implicit measures that allow for an assessment of associative relations only.

  2. Negative affect reduces performance in implicit sequence learning.

    Directory of Open Access Journals (Sweden)

    Junchen Shang

    Full Text Available BACKGROUND: It is well documented that positive rather than negative moods encourage integrative processing of conscious information. However, the extent to which implicit or unconscious learning can be influenced by affective states remains unclear. METHODOLOGY/PRINCIPAL FINDINGS: A Serial Reaction Time (SRT task with sequence structures requiring integration over past trials was adopted to examine the effect of affective states on implicit learning. Music was used to induce and maintain positive and negative affective states. The present study showed that participants in negative rather than positive states learned less of the regularity. Moreover, the knowledge was shown by a Bayesian analysis to be largely unconscious as participants were poor at recognizing the regularity. CONCLUSIONS/SIGNIFICANCE: The results demonstrated that negative rather than positive affect inhibited implicit learning of complex structures. Our findings help to understand the effects of affective states on unconscious or implicit processing.

  3. A recommender system for medical imaging diagnostic.

    Science.gov (United States)

    Monteiro, Eriksson; Valente, Frederico; Costa, Carlos; Oliveira, José Luís

    2015-01-01

    The large volume of data captured daily in healthcare institutions is opening new and great perspectives about the best ways to use it towards improving clinical practice. In this paper we present a context-based recommender system to support medical imaging diagnostic. The system relies on data mining and context-based retrieval techniques to automatically lookup for relevant information that may help physicians in the diagnostic decision.

  4. Mindfulness - en implicit utopi?

    DEFF Research Database (Denmark)

    Nielsen, Anne Maj

    2014-01-01

    The field of mindfulness and meditation has met growing interest in the western world during the last decades. Mindfulness aims to develop a friendly, accepting and mindful awareness in the present moment. Critiques have argued that this aim is deployed in a new kind of management technology where...... mindfulness is used for individualized stress-reduction in order to keep up with existing or worsened working conditions instead of stress-reducing changes in the common working conditions. Mindfulness research emphasizes positive outcomes in coping with demands and challenges in everyday life especially...... considering suffering (for example stress and pain). While explicit constructions of Utopia present ideas of specific societal communities in well-functioning harmony, the interest in mindfulness can in contradistinction be considered an implicit critique of present life-conditions and an “implicit utopia...

  5. A practical implicit finite-difference method: examples from seismic modelling

    International Nuclear Information System (INIS)

    Liu, Yang; Sen, Mrinal K

    2009-01-01

    We derive explicit and new implicit finite-difference formulae for derivatives of arbitrary order with any order of accuracy by the plane wave theory where the finite-difference coefficients are obtained from the Taylor series expansion. The implicit finite-difference formulae are derived from fractional expansion of derivatives which form tridiagonal matrix equations. Our results demonstrate that the accuracy of a (2N + 2)th-order implicit formula is nearly equivalent to that of a (6N + 2)th-order explicit formula for the first-order derivative, and (2N + 2)th-order implicit formula is nearly equivalent to (4N + 2)th-order explicit formula for the second-order derivative. In general, an implicit method is computationally more expensive than an explicit method, due to the requirement of solving large matrix equations. However, the new implicit method only involves solving tridiagonal matrix equations, which is fairly inexpensive. Furthermore, taking advantage of the fact that many repeated calculations of derivatives are performed by the same difference formula, several parts can be precomputed resulting in a fast algorithm. We further demonstrate that a (2N + 2)th-order implicit formulation requires nearly the same memory and computation as a (2N + 4)th-order explicit formulation but attains the accuracy achieved by a (6N + 2)th-order explicit formulation for the first-order derivative and that of a (4N + 2)th-order explicit method for the second-order derivative when additional cost of visiting arrays is not considered. This means that a high-order explicit method may be replaced by an implicit method of the same order resulting in a much improved performance. Our analysis of efficiency and numerical modelling results for acoustic and elastic wave propagation validates the effectiveness and practicality of the implicit finite-difference method

  6. Gender Differences in Implicit and Explicit Memory for Affective Passages

    Science.gov (United States)

    Burton, Leslie A.; Rabin, Laura; Vardy, Susan Bernstein.; Frohlich, Jonathan; Wyatt, Gwinne; Dimitri, Diana; Constante, Shimon; Guterman, Elan

    2004-01-01

    Thirty-two participants were administered 4 verbal tasks, an Implicit Affective Task, an Implicit Neutral Task, an Explicit Affective Task, and an Explicit Neutral Task. For the Implicit Tasks, participants were timed while reading passages aloud as quickly as possible, but not so quickly that they did not understand. A target verbal passage was…

  7. Solving the Bateman equations in CASMO5 using implicit ode numerical methods for stiff systems

    International Nuclear Information System (INIS)

    Hykes, J. M.; Ferrer, R. M.

    2013-01-01

    The Bateman equations, which describe the transmutation of nuclides over time as a result of radioactive decay, absorption, and fission, are often numerically stiff. This is especially true if short-lived nuclides are included in the system. This paper describes the use of implicit numerical methods for o D Es applied to the stiff Bateman equations, specifically employing the Backward Differentiation Formulas (BDF) form of the linear multistep method. As is true in other domains, using an implicit method removes or lessens the (sometimes severe) step-length constraints by which explicit methods must abide. To gauge its accuracy and speed, the BDF method is compared to a variety of other solution methods, including Runge-Kutta explicit methods and matrix exponential methods such as the Chebyshev Rational Approximation Method (CRAM). A preliminary test case was chosen as representative of a PWR lattice depletion step and was solved with numerical libraries called from a Python front-end. The Figure of Merit (a combined measure of accuracy and efficiency) for the BDF method was nearly identical to that for CRAM, while explicit methods and other matrix exponential approximations trailed behind. The test case includes 319 nuclides, in which the shortest-lived nuclide is 98 Nb with a half-life of 2.86 seconds. Finally, the BDF and CRAM methods were compared within CASMO5, where CRAM had a FOM about four times better than BDF, although the BDF implementation was not fully optimized. (authors)

  8. Securities regulation and implicit penalties

    Directory of Open Access Journals (Sweden)

    Donghua Chen

    2011-06-01

    Full Text Available The extant literature offers extensive support for the significant role played by institutions in financial markets, but implicit regulation and monitoring have yet to be examined. This study fills this void in the literature by employing unique Chinese datasets to explore the implicit regulation and penalties imposed by the Chinese government in regulating the initial public offering (IPO market. Of particular interest are the economic consequences of underwriting IPO deals for client firms that violate regulatory rules in China’s capital market. We provide evidence to show that the associated underwriters’ reputations are impaired and their market share declines. We further explore whether such negative consequences result from a market disciplinary mechanism or a penalty imposed by the government. To analyze the possibility of a market disciplinary mechanism at work, we investigate (1 the market reaction to other client firms whose IPO deals were underwritten by underwriters associated with a violation at the time the violation was publicly disclosed and (2 the under-pricing of IPO deals undertaken by these underwriters after such disclosure. To analyze whether the government imposes an implicit penalty, we examine the application processing time for future IPO deals underwritten by the associated underwriters and find it to be significantly longer than for IPO deals underwritten by other underwriters. Overall, there is little evidence to suggest that the market penalizes underwriters for the rule-violating behavior of their client firms in China. Instead, the Chinese government implicitly penalizes them by imposing more stringent criteria on and lengthening the processing time of the IPO deals they subsequently underwrite.

  9. Developmental Differences in Implicit and Explicit Memory Performance.

    Science.gov (United States)

    Perez, Lori A.; Peynircioglu, Zehra F.; Blaxton, Teresa A.

    1998-01-01

    Compared perceptual and conceptual implicit and explicit memory performance of preschool, elementary, and college students. Found that conceptual explicit memory improved with age. Perceptual explicit memory and implicit memory showed no developmental change. Perceptual processing during study led to better performance than conceptual processing…

  10. Semi-implicit surface tension formulation with a Lagrangian surface mesh on an Eulerian simulation grid

    KAUST Repository

    Schroeder, Craig

    2012-02-01

    We present a method for applying semi-implicit forces on a Lagrangian mesh to an Eulerian discretization of the Navier Stokes equations in a way that produces a sparse symmetric positive definite system. The resulting method has semi-implicit and fully-coupled viscosity, pressure, and Lagrangian forces. We apply our new framework for forces on a Lagrangian mesh to the case of a surface tension force, which when treated explicitly leads to a tight time step restriction. By applying surface tension as a semi-implicit Lagrangian force, the resulting method benefits from improved stability and the ability to take larger time steps. The resulting discretization is also able to maintain parasitic currents at low levels. © 2011.

  11. [Psychological theory and implicit sociology.].

    Science.gov (United States)

    Sévigny, R

    1983-01-01

    This text is based on the hypothesis that every theory on the psychology of personality must inevitably, in one manner or another, have a sociological referent, that is to say, it must refer to a body of knowledge which deals with a diversity of social contexts and their relations to individuals. According to this working hypothesis, such a sociology is implicit. This text then discusses a group of theoretical approaches in an effort to verify this hypothesis. This approach allows the extrication of diverse forms or diverse expressions of this implicit sociology within this context several currents are rapidly explored : psychoanalysis, behaviorism, gestalt, classical theory of needs. The author also comments on the approach, inspired by oriental techniques or philosophies, which employs the notion of myth to deepen self awareness. Finally, from the same perspective, he comments at greater length on the work of Carl Rogers, highlighting the diverse form of implicit sociology. In addition to Carl Rogers, this text refers to Freud, Jung, Adler, Reich, Perls, Goodman, Skinner as well as to Ginette Paris and various analysts of Taoism. In conclusion, the author indicates the significance of his analysis from double viewpoint of psychological theory and practice.

  12. Toward textbook multigrid efficiency for fully implicit resistive magnetohydrodynamics

    KAUST Repository

    Adams, Mark F.; Samtaney, Ravi; Brandt, Achi

    2010-01-01

    Multigrid methods can solve some classes of elliptic and parabolic equations to accuracy below the truncation error with a work-cost equivalent to a few residual calculations so-called "textbook" multigrid efficiency. We investigate methods to solve the system of equations that arise in time dependent magnetohydrodynamics (MHD) simulations with textbook multigrid efficiency. We apply multigrid techniques such as geometric interpolation, full approximate storage, Gauss-Seidel smoothers, and defect correction for fully implicit, nonlinear, second-order finite volume discretizations of MHD. We apply these methods to a standard resistive MHD benchmark problem, the GEM reconnection problem, and add a strong magnetic guide field, which is a critical characteristic of magnetically confined fusion plasmas. We show that our multigrid methods can achieve near textbook efficiency on fully implicit resistive MHD simulations. (C) 2010 Elsevier Inc. All rights reserved.

  13. Toward textbook multigrid efficiency for fully implicit resistive magnetohydrodynamics

    KAUST Repository

    Adams, Mark F.

    2010-09-01

    Multigrid methods can solve some classes of elliptic and parabolic equations to accuracy below the truncation error with a work-cost equivalent to a few residual calculations so-called "textbook" multigrid efficiency. We investigate methods to solve the system of equations that arise in time dependent magnetohydrodynamics (MHD) simulations with textbook multigrid efficiency. We apply multigrid techniques such as geometric interpolation, full approximate storage, Gauss-Seidel smoothers, and defect correction for fully implicit, nonlinear, second-order finite volume discretizations of MHD. We apply these methods to a standard resistive MHD benchmark problem, the GEM reconnection problem, and add a strong magnetic guide field, which is a critical characteristic of magnetically confined fusion plasmas. We show that our multigrid methods can achieve near textbook efficiency on fully implicit resistive MHD simulations. (C) 2010 Elsevier Inc. All rights reserved.

  14. Differential patterns of implicit emotional processing in Alzheimer's disease and healthy aging.

    Science.gov (United States)

    García-Rodríguez, Beatriz; Fusari, Anna; Rodríguez, Beatriz; Hernández, José Martín Zurdo; Ellgring, Heiner

    2009-01-01

    Implicit memory for emotional facial expressions (EFEs) was investigated in young adults, healthy old adults, and mild Alzheimer's disease (AD) patients. Implicit memory is revealed by the effect of experience on performance by studying previously encoded versus novel stimuli, a phenomenon referred to as perceptual priming. The aim was to assess the changes in the patterns of priming as a function of aging and dementia. Participants identified EFEs taken from the Facial Action Coding System and the stimuli used represented the emotions of happiness, sadness, surprise, fear, anger, and disgust. In the study phase, participants rated the pleasantness of 36 faces using a Likert-type scale. Subsequently, the response to the 36 previously studied and 36 novel EFEs was tested when they were randomly presented in a cued naming task. The results showed that implicit memory for EFEs is preserved in AD and aging, and no specific age-related effects on implicit memory for EFEs were observed. However, different priming patterns were evident in AD patients that may reflect pathological brain damage and the effect of stimulus complexity. These findings provide evidence of how progressive neuropathological changes in the temporal and frontal areas may affect emotional processing in more advanced stages of the disease.

  15. Production Functions for Water Delivery Systems: Analysis and Estimation Using Dual Cost Function and Implicit Price Specifications

    Science.gov (United States)

    Teeples, Ronald; Glyer, David

    1987-05-01

    Both policy and technical analysis of water delivery systems have been based on cost functions that are inconsistent with or are incomplete representations of the neoclassical production functions of economics. We present a full-featured production function model of water delivery which can be estimated from a multiproduct, dual cost function. The model features implicit prices for own-water inputs and is implemented as a jointly estimated system of input share equations and a translog cost function. Likelihood ratio tests are performed showing that a minimally constrained, full-featured production function is a necessary specification of the water delivery operations in our sample. This, plus the model's highly efficient and economically correct parameter estimates, confirms the usefulness of a production function approach to modeling the economic activities of water delivery systems.

  16. A Recommender System in the Cyber Defense Domain

    Science.gov (United States)

    2014-03-27

    monitoring software is a java based program sending updates to the database on the sensor machine. The host monitoring program gathers information about...3.2.2 Database. A MySQL database located on the sensor machine acts as the storage for the sensors on the network. Snort, Nmap, vulnerability scores, and...machine with the IDS and the recommender is labeled “sensor”. The recommender system code is written in java and compiled using java version 1.6.024

  17. Solving the apparent diversity-accuracy dilemma of recommender systems.

    Science.gov (United States)

    Zhou, Tao; Kuscsik, Zoltán; Liu, Jian-Guo; Medo, Matús; Wakeling, Joseph Rushton; Zhang, Yi-Cheng

    2010-03-09

    Recommender systems use data on past user preferences to predict possible future likes and interests. A key challenge is that while the most useful individual recommendations are to be found among diverse niche objects, the most reliably accurate results are obtained by methods that recommend objects based on user or object similarity. In this paper we introduce a new algorithm specifically to address the challenge of diversity and show how it can be used to resolve this apparent dilemma when combined in an elegant hybrid with an accuracy-focused algorithm. By tuning the hybrid appropriately we are able to obtain, without relying on any semantic or context-specific information, simultaneous gains in both accuracy and diversity of recommendations.

  18. EdgeMaps: visualizing explicit and implicit relations

    Science.gov (United States)

    Dörk, Marian; Carpendale, Sheelagh; Williamson, Carey

    2011-01-01

    In this work, we introduce EdgeMaps as a new method for integrating the visualization of explicit and implicit data relations. Explicit relations are specific connections between entities already present in a given dataset, while implicit relations are derived from multidimensional data based on shared properties and similarity measures. Many datasets include both types of relations, which are often difficult to represent together in information visualizations. Node-link diagrams typically focus on explicit data connections, while not incorporating implicit similarities between entities. Multi-dimensional scaling considers similarities between items, however, explicit links between nodes are not displayed. In contrast, EdgeMaps visualize both implicit and explicit relations by combining and complementing spatialization and graph drawing techniques. As a case study for this approach we chose a dataset of philosophers, their interests, influences, and birthdates. By introducing the limitation of activating only one node at a time, interesting visual patterns emerge that resemble the aesthetics of fireworks and waves. We argue that the interactive exploration of these patterns may allow the viewer to grasp the structure of a graph better than complex node-link visualizations.

  19. Implicit versus explicit : An ACT-R learning perspective

    NARCIS (Netherlands)

    Taatgen, N.A.

    1999-01-01

    Dienes & Perner propose a theory of implicit and explicit knowledge that is not entirely complete. It does not address many of the empirical issues, nor does it explain the difference between implicit and explicit learning. It does, however, provide a possible unified explanation, as opposed to the

  20. Implicit visual learning and the expression of learning.

    Science.gov (United States)

    Haider, Hilde; Eberhardt, Katharina; Kunde, Alexander; Rose, Michael

    2013-03-01

    Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response devices (keyboard vs. mouse) in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. Implementation Intentions Reduce Implicit Stereotype Activation and Application.

    Science.gov (United States)

    Rees, Heather Rose; Rivers, Andrew Michael; Sherman, Jeffrey W

    2018-05-01

    Research has found that implementation intentions, if-then action plans (e.g., "if I see a Black face, I will think safe"), reduce stereotyping on implicit measures. However, it is unknown by what process(es) implementation intentions reduce implicit stereotyping. The present research examines the effects of implementation intentions on stereotype activation (e.g., extent to which stereotypic information is accessible) and stereotype application (e.g., extent to which accessible stereotypes are applied in judgment). In addition, we assessed the efficiency of implementation intentions by manipulating cognitive resources (e.g., digit-span, restricted response window) while participants made judgments on an implicit stereotyping measure. Across four studies, implementation intentions reduced implicit stereotyping. This decrease in stereotyping was associated with reductions in both stereotype activation and application. In addition, these effects of implementation intentions were highly efficient and associated with reduced stereotyping even for groups for which people may have little practice inhibiting stereotypes (e.g., gender).

  2. Is homophobia associated with an implicit same-sex attraction?

    Science.gov (United States)

    Macinnis, Cara C; Hodson, Gordon

    2013-01-01

    Some theorists propose that homophobia stems from underlying same-sex attraction. A few studies have tested this hypothesis, yet without a clear measure of implicit sexual attraction, producing mixed results. For the first time, we test this attraction-based account of homophobia among both men and women using an implicit measure of sexual attraction. No evidence of an attraction-based account of homophobia emerged. Instead, implicit same-sex attraction was related to positive evaluations of gay men and lesbians among female participants. Even in targeted analyses examining the relation between implicit same-sex attraction and homosexual evaluations among only those theoretically most likely to demonstrate an attraction-based homophobic effect, implicit same-sex attraction was not associated with evaluations of homosexuals or was associated with more positive evaluations of homosexuals. In addition, explicit same-sex attraction was related to positive evaluations of gay men and lesbians for male participants. These results are more in keeping with the attitude-similarity effect (i.e., people like, rather than dislike, similar others).

  3. [GRADE system: classification of quality of evidence and strength of recommendation].

    Science.gov (United States)

    Aguayo-Albasini, José Luis; Flores-Pastor, Benito; Soria-Aledo, Víctor

    2014-02-01

    The acquisition and classification of scientific evidence, and subsequent formulation of recommendations constitute the basis for the development of clinical practice guidelines. There are several systems for the classification of evidence and strength of recommendations; the most commonly used nowadays is the Grading of Recommendations, Assessment, Development and Evaluation system (GRADE). The GRADE system initially classifies the evidence into high or low, coming from experimental or observational studies; subsequently and following a series of considerations, the evidence is classified into high, moderate, low or very low. The strength of recommendations is based not only on the quality of the evidence, but also on a series of factors such as the risk/benefit balance, values and preferences of the patients and professionals, and the use of resources or costs. Copyright © 2013 AEC. Published by Elsevier Espana. All rights reserved.

  4. Efficient privacy-enhanced familiarity-based recommender system

    NARCIS (Netherlands)

    Jeckmans, Arjan; Peter, Andreas; Hartel, Pieter H.

    Recommender systems can help users to find interesting content, often based on similarity with other users. However, studies have shown that in some cases familiarity gives comparable results to similarity. Using familiarity has the added bonus of increasing privacy between users and utilizing a

  5. Measuring Systematic Risk Using Implicit Beta

    OpenAIRE

    Andrew F. Siegel

    1995-01-01

    A new technology is proposed for estimating the systematic (beta) risk of a firm's stock. Just as the implicit volatility of an asset is revealed by an ordinary call option, the "implicit beta" of a stock would be revealed by the price of an option to exchange shares of stock for shares of a market index. Considerable benefits would accrue to those involved with the theory and practice of finance, if and when these exchange options begin trading, due to the availability of instantaneous, up-t...

  6. Music recommendation system for biofied building considering multiple residents

    Science.gov (United States)

    Ito, Takahiro; Mita, Akira

    2012-04-01

    This research presents a music recommendation system based on multiple users' communication excitement and productivity. Evaluation is conducted on following two points. 1, Does songA recommended by the system improve the situation of dropped down communication excitement? 2, Does songB recommended by the system improve the situation of dropped down and productivity of collaborative work? The objective of this system is to recommend songs which shall improve the situation of dropped down communication excitement and productivity. Songs are characterized according to three aspects; familiarity, relaxing and BPM(Beat Per Minutes). Communication excitement is calculated from speech data obtained by an audio sensor. Productivity of collaborative brainstorming is manually calculated by the number of time-series key words during mind mapping. First experiment was music impression experiment to 118 students. Based on 1, average points of familiarity, relaxing and BPM 2, cronbach alpha factor, songA(high familiarity, high relaxing and high BPM song) and songB(high familiarity, high relaxing and low BPM) are selected. Exploratory experiment defined dropped down communication excitement and dropped down and productivity of collaborative work. Final experiment was conducted to 32 first meeting students divided into 8 groups. First 4 groups had mind mapping 1 while listening to songA, then had mind mapping 2 while listening songB. Following 4 groups had mind mapping 1 while listening to songB, then had mind mapping 2 while listening songA. Fianl experiment shows two results. Firstly, ratio of communication excitement between music listening section and whole brain storming is 1.27. Secondly, this system increases 69% of average productivity.

  7. Opinion-enhanced collaborative filtering for recommender systems through sentiment analysis

    Science.gov (United States)

    Wang, Wei; Wang, Hongwei

    2015-10-01

    The motivation of collaborative filtering (CF) comes from the idea that people often get the best recommendations from someone with similar tastes. With the growing popularity of opinion-rich resources such as online reviews, new opportunities arise as we can identify the preferences from user opinions. The main idea of our approach is to elicit user opinions from online reviews, and map such opinions into preferences that can be understood by CF-based recommender systems. We divide recommender systems into two types depending on the number of product category recommended: the multiple-category recommendation and the single-category recommendation. For the former, sentiment polarity in coarse-grained manner is identified while for the latter fine-grained sentiment analysis is conducted for each product aspect. If the evaluation frequency for an aspect by a user is greater than the average frequency by all users, it indicates that the user is more concerned with that aspect. If a user's rating for an aspect is lower than the average rating by all users, he or she is much pickier than others on that aspect. Through sentiment analysis, we then build an opinion-enhanced user preference model, where the higher the similarity between user opinions the more consistent preferences between users are. Experiment results show that the proposed CF algorithm outperforms baseline methods for product recommendation in terms of accuracy and recall.

  8. Existence and Stability of Solutions for Implicit Multivalued Vector Equilibrium Problems

    Directory of Open Access Journals (Sweden)

    Li Qiuying

    2011-01-01

    Full Text Available A class of implicit multivalued vector equilibrium problems is studied. By using the generalized Fan-Browder fixed point theorem, some existence results of solutions for the implicit multivalued vector equilibrium problems are obtained under some suitable assumptions. Moreover, a stability result of solutions for the implicit multivalued vector equilibrium problems is derived. These results extend and unify some recent results for implicit vector equilibrium problems, multivalued vector variational inequality problems, and vector variational inequality problems.

  9. Multigrid methods for fully implicit oil reservoir simulation

    Energy Technology Data Exchange (ETDEWEB)

    Molenaar, J.

    1995-12-31

    In this paper, the authors consider the simultaneous flow of oil and water in reservoir rock. This displacement process is modeled by two basic equations the material balance or continuity equations, and the equation of motion (Darcy`s law). For the numerical solution of this system of nonlinear partial differential equations, there are two approaches: the fully implicit or simultaneous solution method, and the sequential solution method. In this paper, the authors consider the possibility of applying multigrid methods for the iterative solution of the systems of nonlinear equations.

  10. A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users.

    Science.gov (United States)

    Ravi, Logesh; Vairavasundaram, Subramaniyaswamy

    2016-01-01

    Rapid growth of web and its applications has created a colossal importance for recommender systems. Being applied in various domains, recommender systems were designed to generate suggestions such as items or services based on user interests. Basically, recommender systems experience many issues which reflects dwindled effectiveness. Integrating powerful data management techniques to recommender systems can address such issues and the recommendations quality can be increased significantly. Recent research on recommender systems reveals an idea of utilizing social network data to enhance traditional recommender system with better prediction and improved accuracy. This paper expresses views on social network data based recommender systems by considering usage of various recommendation algorithms, functionalities of systems, different types of interfaces, filtering techniques, and artificial intelligence techniques. After examining the depths of objectives, methodologies, and data sources of the existing models, the paper helps anyone interested in the development of travel recommendation systems and facilitates future research direction. We have also proposed a location recommendation system based on social pertinent trust walker (SPTW) and compared the results with the existing baseline random walk models. Later, we have enhanced the SPTW model for group of users recommendations. The results obtained from the experiments have been presented.

  11. Environmental context effects in conceptual explicit and implicit memory.

    Science.gov (United States)

    Parker, Andrew; Dagnall, Neil; Coyle, Anne-Marie

    2007-05-01

    Previous research has found environmental context effects for both conceptual explicit and conceptual implicit memory (Parker, Gellatly, & Waterman, 1999). The research presented here challenges these findings on methodological grounds. Experiment 1 assessed the effects of context change on category-exemplar generation (conceptual implicit memory test) and category-cued recall (conceptual explicit memory test). Experiment 2 assessed the effects of context change on word association (conceptual implicit memory test) and word associate cued recall (conceptual explicit memory test). In both experiments, study-test changes in environmental context were found to influence performance only on tests of explicit memory. It is concluded that when retrieval cues across explicit and implicit tests are matched, and the probability of explicit contamination is reduced, then only conceptual explicit test performance is reduced by study-test changes in environmental context.

  12. Ranking and Context-awareness in Recommender Systems

    NARCIS (Netherlands)

    Shi, Y.

    2013-01-01

    In this thesis we report the results of our research on recommender systems, which addresses some of the critical scientific challenges that still remain open in this domain. Collaborative filtering (CF) is the most common technique of predicting the interests of a user by collecting preference

  13. Recommender System for Sales at Material Store Using Fuzzy Tsukamoto

    Directory of Open Access Journals (Sweden)

    July Kurniawan

    2016-02-01

    Full Text Available The retail business has developed very rapidly, especially in Indonesia. One of them is material stores that have not applied the technology and still manual. In this modern era of buying and selling consumers need systems to assist in overcoming problems in terms of recommend items based on customer needs. The aim of this study is to determine the needs of consumers to recommend the necessary consumer goods. This system will simplify these processes, by utilizing information technology using Tsukamoto fuzzy logic. So that consumer demand for faster and more accurate in recommending goods could be accommodated. This research outlines what is needed to overcome the problems that had been experienced by consumers with a lack of information. The recommendations of this study is the form that refers to the percentage of goods from the predictions that have been studied previously.

  14. A Conceptual Framework for Evolving, Recommender Online Learning Systems

    Science.gov (United States)

    Peiris, K. Dharini Amitha; Gallupe, R. Brent

    2012-01-01

    A comprehensive conceptual framework is developed and described for evolving recommender-driven online learning systems (ROLS). This framework describes how such systems can support students, course authors, course instructors, systems administrators, and policy makers in developing and using these ROLS. The design science information systems…

  15. The Myth of Objectivity: Implicit Racial Bias and the Law (Part 1

    Directory of Open Access Journals (Sweden)

    Willem Hendrik Gravett

    2017-03-01

    Full Text Available The centrality of race to our history and the substantial racial inequalities that continue to pervade society ensure that "race" remains an extraordinarily salient and meaningful social category. Explicit racial prejudice, however, is only part of the problem. Equally important - and likely more pervasive - is the phenomenon of implicit racial prejudice: the cognitive processes whereby, despite even our best intentions, the human mind automatically classifies information in racial categories and against disfavoured social groups. Empirical research shows convincingly that these biases against socially disfavoured groups are (i pervasive; (ii often diverge from consciously reported attitudes and beliefs; and (iii influence consequential behaviour towards the subjects of these biases. The existence of implicit racial prejudices poses a challenge to legal theory and practice. From the standpoint of a legal system that seeks to forbid differential treatment based upon race or other protected traits, if people are in fact treated differently, and worse, because of their race or other protected trait, then the fundamental principle of anti-discrimination has been violated. It hardly matters that the source of the differential treatment is implicit rather than conscious bias. This article investigates the relevance of this research to the law by means of an empirical account of how implicit racial bias could affect the criminal trial trajectory in the areas of policing, prosecutorial discretion and judicial decision-making. It is the author's hypothesis that this mostly American research also applies to South Africa. The empirical evidence of implicit biases in every country tested shows that people are systematically implicitly biased in favour of socially privileged groups. Even after 1994 South Africa – similar to the US – continues to be characterised by a pronounced social hierarchy in which Whites overwhelmingly have the highest social

  16. The Myth of Objectivity: Implicit Racial Bias and the Law (Part 2

    Directory of Open Access Journals (Sweden)

    Willem Hendrik Gravett

    2017-04-01

    Full Text Available The centrality of race to our history and the substantial racial inequalities that continue to pervade society ensure that "race" remains an extraordinarily salient and meaningful social category. Explicit racial prejudice, however, is only part of the problem. Equally important - and likely more pervasive - is the phenomenon of implicit racial prejudice: the cognitive processes whereby, despite even our best intentions, the human mind automatically classifies information in racial categories and against disfavoured social groups. Empirical research shows convincingly that these biases against socially disfavoured groups are (i pervasive; (ii often diverge from consciously reported attitudes and beliefs; and (iii influence consequential behaviour towards the subjects of these biases. The existence of implicit racial prejudices poses a challenge to legal theory and practice. From the standpoint of a legal system that seeks to forbid differential treatment based upon race or other protected traits, if people are in fact treated differently, and worse, because of their race or other protected trait, then the fundamental principle of anti-discrimination has been violated. It hardly matters that the source of the differential treatment is implicit rather than conscious bias. This article investigates the relevance of this research to the law by means of an empirical account of how implicit racial bias could affect the criminal trial trajectory in the areas of policing, prosecutorial discretion and judicial decision-making. It is the author's hypothesis that this mostly American research also applies to South Africa. The empirical evidence of implicit biases in every country tested shows that people are systematically implicitly biased in favour of socially privileged groups. Even after 1994 South Africa – similar to the US – continues to be characterised by a pronounced social hierarchy in which Whites overwhelmingly have the highest social

  17. Implicit sequence learning in people with Parkinson’s disease

    Directory of Open Access Journals (Sweden)

    Katherine R Gamble

    2014-08-01

    Full Text Available Implicit sequence learning involves learning about dependencies in sequences of events without intent to learn or awareness of what has been learned. Sequence learning is related to striatal dopamine levels, striatal activation, and integrity of white matter connections. People with Parkinson’s disease (PD have degeneration of dopamine-producing neurons, leading to dopamine deficiency and therefore striatal deficits, and they have difficulties with sequencing, including complex language comprehension and postural stability. Most research on implicit sequence learning in PD has used motor-based tasks. However, because PD presents with motor deficits, it is difficult to assess whether learning itself is impaired in these tasks. The present study used an implicit sequence learning task with a reduced motor component, the Triplets Learning Task (TLT. People with PD and age- and education-matched healthy older adults completed three sessions (each consisting of 10 blocks of 50 trials of the TLT. Results revealed that the PD group was able to learn the sequence, however, when learning was examined using a Half Blocks analysis (Nemeth et al., 2013, which compared learning in the 1st 25/50 trials of all blocks to that in the 2nd 25/50 trials, the PD group showed significantly less learning than Controls in the 2nd Half Blocks, but not in the 1st. Nemeth et al. hypothesized that the 1st Half Blocks involve recall and reactivation of the sequence learned, thus reflecting hippocampal-dependent learning, while the 2nd Half Blocks involve proceduralized behavior of learned sequences, reflecting striatal-based learning. The present results suggest that the PD group had intact hippocampal-dependent implicit sequence learning, but impaired striatal-dependent learning. Thus, sequencing deficits in PD are likely due to striatal impairments, but other brain systems, such as the hippocampus, may be able to partially compensate for striatal decline to improve

  18. Consumers’ intention to use health recommendation systems to receive personalized nutrition advice

    NARCIS (Netherlands)

    S. Wendel (Sonja); B.G.C. Dellaert (Benedict); A. Ronteltap (Amber); H.C.M. van Trijp (Hans)

    2013-01-01

    markdownabstract__Abstract__ __Background:__ Sophisticated recommendation systems are used more and more in the health sector to assist consumers in healthy decision making. In this study we investigate consumers' evaluation of hypothetical health recommendation systems that provide

  19. Enabling Open Research Data Discovery through a Recommender System

    Science.gov (United States)

    Devaraju, Anusuriya; Jayasinghe, Gaya; Klump, Jens; Hogan, Dominic

    2017-04-01

    Government agencies, universities, research and nonprofit organizations are increasingly publishing their datasets to promote transparency, induce new research and generate economic value through the development of new products or services. The datasets may be downloaded from various data portals (data repositories) which are general or domain-specific. The Registry of Research Data Repository (re3data.org) lists more than 2500 such data repositories from around the globe. Data portals allow keyword search and faceted navigation to facilitate discovery of research datasets. However, the volume and variety of datasets have made finding relevant datasets more difficult. Common dataset search mechanisms may be time consuming, may produce irrelevant results and are primarily suitable for users who are familiar with the general structure and contents of the respective database. Therefore, we need new approaches to support research data discovery. Recommender systems offer new possibilities for users to find datasets that are relevant to their research interests. This study presents a recommender system developed for the CSIRO Data Access Portal (DAP, http://data.csiro.au). The datasets hosted on the portal are diverse, published by researchers from 13 business units in the organisation. The goal of the study is not to replace the current search mechanisms on the data portal, but rather to extend the data discovery through an exploratory search, in this case by building a recommender system. We adopted a hybrid recommendation approach, comprising content-based filtering and item-item collaborative filtering. The content-based filtering computes similarities between datasets based on metadata such as title, keywords, descriptions, fields of research, location, contributors, etc. The collaborative filtering utilizes user search behaviour and download patterns derived from the server logs to determine similar datasets. Similarities above are then combined with different

  20. Applications of implicit restarting in optimization and control Dan Sorensen

    Energy Technology Data Exchange (ETDEWEB)

    Sorensen, D. [Rice Univ., Houston, TX (United States)

    1996-12-31

    Implicit restarting is a technique for combining the implicitly shifted QR mechanism with a k-step Arnoldi or Lanczos factorization to obtain a truncated form of the implicitly shifted QR-iteration suitable for large scale eigenvalue problems. The software package ARPACK based upon this technique has been successfully used to solve large scale symmetric and nonsymmetric (generalized) eigenvalue problems arising from a variety of applications.

  1. The effect of encoding duration on implicit and explicit eyewitness memory.

    Science.gov (United States)

    Carol, Rolando N; Schreiber Compo, Nadja

    2018-05-01

    The present study investigated the effect of encoding duration on implicit and explicit eyewitness memory. Participants (N = 227) viewed a mock crime (brief, 15-s vs. long, 30-s vs. irrelevant/control) and were then tested with both implicit and explicit memory prompts or with explicit memory prompts only. Brief-encoding participants revealed more critical details implicitly than long-encoding or control participants. Further, the number and percentage of accurate details recalled explicitly were higher for long-encoding than for brief-encoding participants. Implicit testing prior to explicit recall-as compared to completing a filler task-was detrimental to free recall performance. Interestingly, brief-encoding participants were significantly more likely to remember critical details implicitly but not explicitly than long-encoding participants. This is the first study to investigate implicit eyewitness memory for a multimodal mock crime. Findings are theoretically consistent with prior research on cognition while expanding upon the extant eyewitness memory and investigative interviewing literature. Published by Elsevier Inc.

  2. Implicit structured sequence learning: an fMRI study of the structural mere-exposure effect.

    Science.gov (United States)

    Folia, Vasiliki; Petersson, Karl Magnus

    2014-01-01

    In this event-related fMRI study we investigated the effect of 5 days of implicit acquisition on preference classification by means of an artificial grammar learning (AGL) paradigm based on the structural mere-exposure effect and preference classification using a simple right-linear unification grammar. This allowed us to investigate implicit AGL in a proper learning design by including baseline measurements prior to grammar exposure. After 5 days of implicit acquisition, the fMRI results showed activations in a network of brain regions including the inferior frontal (centered on BA 44/45) and the medial prefrontal regions (centered on BA 8/32). Importantly, and central to this study, the inclusion of a naive preference fMRI baseline measurement allowed us to conclude that these fMRI findings were the intrinsic outcomes of the learning process itself and not a reflection of a preexisting functionality recruited during classification, independent of acquisition. Support for the implicit nature of the knowledge utilized during preference classification on day 5 come from the fact that the basal ganglia, associated with implicit procedural learning, were activated during classification, while the medial temporal lobe system, associated with explicit declarative memory, was consistently deactivated. Thus, preference classification in combination with structural mere-exposure can be used to investigate structural sequence processing (syntax) in unsupervised AGL paradigms with proper learning designs.

  3. A System Computational Model of Implicit Emotional Learning.

    Science.gov (United States)

    Puviani, Luca; Rama, Sidita

    2016-01-01

    Nowadays, the experimental study of emotional learning is commonly based on classical conditioning paradigms and models, which have been thoroughly investigated in the last century. Unluckily, models based on classical conditioning are unable to explain or predict important psychophysiological phenomena, such as the failure of the extinction of emotional responses in certain circumstances (for instance, those observed in evaluative conditioning, in post-traumatic stress disorders and in panic attacks). In this manuscript, starting from the experimental results available from the literature, a computational model of implicit emotional learning based both on prediction errors computation and on statistical inference is developed. The model quantitatively predicts (a) the occurrence of evaluative conditioning, (b) the dynamics and the resistance-to-extinction of the traumatic emotional responses, (c) the mathematical relation between classical conditioning and unconditioned stimulus revaluation. Moreover, we discuss how the derived computational model can lead to the development of new animal models for resistant-to-extinction emotional reactions and novel methodologies of emotions modulation.

  4. Learning to Recommend Point-of-Interest with the Weighted Bayesian Personalized Ranking Method in LBSNs

    OpenAIRE

    Lei Guo; Haoran Jiang; Xinhua Wang; Fangai Liu

    2017-01-01

    Point-of-interest (POI) recommendation has been well studied in recent years. However, most of the existing methods focus on the recommendation scenarios where users can provide explicit feedback. In most cases, however, the feedback is not explicit, but implicit. For example, we can only get a user’s check-in behaviors from the history of what POIs she/he has visited, but never know how much she/he likes and why she/he does not like them. Recently, some researchers have noticed this problem ...

  5. A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users

    Directory of Open Access Journals (Sweden)

    Logesh Ravi

    2016-01-01

    Full Text Available Rapid growth of web and its applications has created a colossal importance for recommender systems. Being applied in various domains, recommender systems were designed to generate suggestions such as items or services based on user interests. Basically, recommender systems experience many issues which reflects dwindled effectiveness. Integrating powerful data management techniques to recommender systems can address such issues and the recommendations quality can be increased significantly. Recent research on recommender systems reveals an idea of utilizing social network data to enhance traditional recommender system with better prediction and improved accuracy. This paper expresses views on social network data based recommender systems by considering usage of various recommendation algorithms, functionalities of systems, different types of interfaces, filtering techniques, and artificial intelligence techniques. After examining the depths of objectives, methodologies, and data sources of the existing models, the paper helps anyone interested in the development of travel recommendation systems and facilitates future research direction. We have also proposed a location recommendation system based on social pertinent trust walker (SPTW and compared the results with the existing baseline random walk models. Later, we have enhanced the SPTW model for group of users recommendations. The results obtained from the experiments have been presented.

  6. A Collaborative Location Based Travel Recommendation System through Enhanced Rating Prediction for the Group of Users

    Science.gov (United States)

    Ravi, Logesh; Vairavasundaram, Subramaniyaswamy

    2016-01-01

    Rapid growth of web and its applications has created a colossal importance for recommender systems. Being applied in various domains, recommender systems were designed to generate suggestions such as items or services based on user interests. Basically, recommender systems experience many issues which reflects dwindled effectiveness. Integrating powerful data management techniques to recommender systems can address such issues and the recommendations quality can be increased significantly. Recent research on recommender systems reveals an idea of utilizing social network data to enhance traditional recommender system with better prediction and improved accuracy. This paper expresses views on social network data based recommender systems by considering usage of various recommendation algorithms, functionalities of systems, different types of interfaces, filtering techniques, and artificial intelligence techniques. After examining the depths of objectives, methodologies, and data sources of the existing models, the paper helps anyone interested in the development of travel recommendation systems and facilitates future research direction. We have also proposed a location recommendation system based on social pertinent trust walker (SPTW) and compared the results with the existing baseline random walk models. Later, we have enhanced the SPTW model for group of users recommendations. The results obtained from the experiments have been presented. PMID:27069468

  7. Development of a Recommender System based on Personal History

    Science.gov (United States)

    Tanaka, Katsuaki; Hori, Koichi; Yamamoto, Masato

    The flood of information on the Internet makes a person who surf it without some strong intention strayed into it. One of the ways to control the balance between a person and the flood is a recommender system by computer, and many web sites use it. These systems work on a web site for the same kind of items. However the field of personal activity is not limited to handle the same kind of thing and a web site, but also offline area in the real world. To handle personal offline activities, LifeLog is proposed as method to record it, but the main purpose of LifeLog is recording a personal history. How to use a history has still been studied stage. The authors have developed a recommender system that captures personal context from history of personal online and offline activities, treats information on web sites as a large set of context, and finds out and extends overlap of them, then recommends information located there. The aim of the system is that a person can enjoy waves of information again. The system worked as a part of My-life Assist Service. It was a service for mobile phones provided by NTT DoCoMo, Inc. as a field experiment from Dec. 2007 to Feb. 2008.

  8. AN INVESTIGATION OF IMPLICIT MEMORY THROUGH LEFT TEMPORAL LOBECTOMY FOR EPILEPSY

    Science.gov (United States)

    Tracy, Joseph I.; Osipowicz, Karol; Godofsky, Samuel; Shah, Atif; Khan, Waseem; Sharan, Ashwini; Sperling, Michael R.

    2012-01-01

    Temporal lobe epilepsy patients have demonstrated a relative preservation in the integrity of implicit memory procedures. We examined performance in a verbal implicit and explicit memory task in left anterior temporal lobectomy patients (LATL) and healthy normal controls (NC) while undergoing fMRI. We hypothesized that despite the relative integrity of implicit memory in both the LATL patients and normal controls, the two groups would show distinct functional neuroanatomic profiles during implicit memory. LATLs and NCs performed Jacoby’s Process Dissociation Process (PDP) procedure during fMRI, requiring completion of word stems based on the previously studied words or new/unseen words. Measures of automaticity and recollection provided uncontaminated indices of implicit and explicit memory, respectively. The behavioral data showed that in the face of temporal lobe pathology implicit memory can be carried out, suggesting implicit verbal memory retrieval is non-mesial temporal in nature. Compared to NCs, the LATL patients showed reliable activation, not deactivation, during implicit (automatic) responding. The regions mediating this response were cortical (left medial frontal and precuneus) and striatal. The active regions in LATL patients have the capacity to implement associative, conditioned responses that might otherwise be carried out by a healthy temporal lobe, suggesting this represented a compensatory activity. Because the precuneus has also been implicated in explicit memory, the data suggests this structure may have a highly flexible functionality, capable of supporting implementation of either explicit memory, or automatic processes such as implicit memory retrieval. Our data suggest that a healthy mesial/anterior temporal lobe may be needed for generating the posterior deactivation perceptual priming response seen in normals. PMID:22981890

  9. a Context-Aware Tourism Recommender System Based on a Spreading Activation Method

    Science.gov (United States)

    Bahramian, Z.; Abbaspour, R. Ali; Claramunt, C.

    2017-09-01

    Users planning a trip to a given destination often search for the most appropriate points of interest location, this being a non-straightforward task as the range of information available is very large and not very well structured. The research presented by this paper introduces a context-aware tourism recommender system that overcomes the information overload problem by providing personalized recommendations based on the user's preferences. It also incorporates contextual information to improve the recommendation process. As previous context-aware tourism recommender systems suffer from a lack of formal definition to represent contextual information and user's preferences, the proposed system is enhanced using an ontology approach. We also apply a spreading activation technique to contextualize user preferences and learn the user profile dynamically according to the user's feedback. The proposed method assigns more effect in the spreading process for nodes which their preference values are assigned directly by the user. The results show the overall performance of the proposed context-aware tourism recommender systems by an experimental application to the city of Tehran.

  10. A CONTEXT-AWARE TOURISM RECOMMENDER SYSTEM BASED ON A SPREADING ACTIVATION METHOD

    Directory of Open Access Journals (Sweden)

    Z. Bahramian

    2017-09-01

    Full Text Available Users planning a trip to a given destination often search for the most appropriate points of interest location, this being a non-straightforward task as the range of information available is very large and not very well structured. The research presented by this paper introduces a context-aware tourism recommender system that overcomes the information overload problem by providing personalized recommendations based on the user’s preferences. It also incorporates contextual information to improve the recommendation process. As previous context-aware tourism recommender systems suffer from a lack of formal definition to represent contextual information and user’s preferences, the proposed system is enhanced using an ontology approach. We also apply a spreading activation technique to contextualize user preferences and learn the user profile dynamically according to the user’s feedback. The proposed method assigns more effect in the spreading process for nodes which their preference values are assigned directly by the user. The results show the overall performance of the proposed context-aware tourism recommender systems by an experimental application to the city of Tehran.

  11. Consumers’ intention to use health recommendation systems to receive personalized nutrition advice

    NARCIS (Netherlands)

    Wendel, S.; Dellaert, B.G.C.; Ronteltap, A.; Trijp, van J.C.M.

    2013-01-01

    Background: Sophisticated recommendation systems are used more and more in the health sector to assist consumers in healthy decision making. In this study we investigate consumers' evaluation of hypothetical health recommendation systems that provide personalized nutrition advice. We examine

  12. Consumers' intention to use health recommendation systems to receive personalized nutrition advice

    NARCIS (Netherlands)

    S. Wendel (Sonja); B.G.C. Dellaert (Benedict); A. Ronteltap (Amber); H.C.M. van Trijp (Hans)

    2013-01-01

    textabstractBackground: Sophisticated recommendation systems are used more and more in the health sector to assist consumers in healthy decision making. In this study we investigate consumers' evaluation of hypothetical health recommendation systems that provide personalized nutrition advice. We

  13. Implicit particle simulation of electromagnetic plasma phenomena

    International Nuclear Information System (INIS)

    Kamimura, T.; Montalvo, E.; Barnes, D.C.; Leboeuf, J.N.; Tajima, T.

    1986-11-01

    A direct method for the implicit particle simulation of electromagnetic phenomena in magnetized, multi-dimensional plasmas is developed. The method is second-order accurate for ωΔt < 1, with ω a characteristic frequency and time step Δt. Direct time integration of the implicit equations with simplified space differencing allows the consistent inclusion of finite particle size. Decentered time differencing of the Lorentz force permits the efficient simulation of strongly magnetized plasmas. A Fourier-space iterative technique for solving the implicit field corrector equation, based on the separation of plasma responses perpendicular and parallel to the magnetic field and longitudinal and transverse to the wavevector, is described. Wave propagation properties in a uniform plasma are in excellent agreement with theoretical expectations. Applications to collisionless tearing and coalescence instabilities further demonstrate the usefulness of the algorithm. (author)

  14. Long-term effects of user preference-oriented recommendation method on the evolution of online system

    Science.gov (United States)

    Shi, Xiaoyu; Shang, Ming-Sheng; Luo, Xin; Khushnood, Abbas; Li, Jian

    2017-02-01

    As the explosion growth of Internet economy, recommender system has become an important technology to solve the problem of information overload. However, recommenders are not one-size-fits-all, different recommenders have different virtues, making them be suitable for different users. In this paper, we propose a novel personalized recommender based on user preferences, which allows multiple recommenders to exist in E-commerce system simultaneously. We find that output of a recommender to each user is quite different when using different recommenders, the recommendation accuracy can be significantly improved if each user is assigned with his/her optimal personalized recommender. Furthermore, different from previous works focusing on short-term effects on recommender, we also evaluate the long-term effect of the proposed method by modeling the evolution of mutual feedback between user and online system. Finally, compared with single recommender running on the online system, the proposed method can improve the accuracy of recommendation significantly and get better trade-offs between short- and long-term performances of recommendation.

  15. The Ms. Stereotype Revisited: Implicit and Explicit Facets

    Science.gov (United States)

    Malcolmson, Kelly A.; Sinclair, Lisa

    2007-01-01

    Implicit and explicit stereotypes toward the title Ms. were examined. Participants read a short description of a target person whose title of address varied (Ms., Mrs., Miss, Mr.). They then rated the person on agentic and communal traits and completed an Implicit Association Test. Replicating earlier research (Dion, 1987), at an explicit level,…

  16. The power of ground user in recommender systems.

    Directory of Open Access Journals (Sweden)

    Yanbo Zhou

    Full Text Available Accuracy and diversity are two important aspects to evaluate the performance of recommender systems. Two diffusion-based methods were proposed respectively inspired by the mass diffusion (MD and heat conduction (HC processes on networks. It has been pointed out that MD has high recommendation accuracy yet low diversity, while HC succeeds in seeking out novel or niche items but with relatively low accuracy. The accuracy-diversity dilemma is a long-term challenge in recommender systems. To solve this problem, we introduced a background temperature by adding a ground user who connects to all the items in the user-item bipartite network. Performing the HC algorithm on the network with ground user (GHC, it showed that the accuracy can be largely improved while keeping the diversity. Furthermore, we proposed a weighted form of the ground user (WGHC by assigning some weights to the newly added links between the ground user and the items. By turning the weight as a free parameter, an optimal value subject to the highest accuracy is obtained. Experimental results on three benchmark data sets showed that the WGHC outperforms the state-of-the-art method MD for both accuracy and diversity.

  17. The power of ground user in recommender systems.

    Science.gov (United States)

    Zhou, Yanbo; Lü, Linyuan; Liu, Weiping; Zhang, Jianlin

    2013-01-01

    Accuracy and diversity are two important aspects to evaluate the performance of recommender systems. Two diffusion-based methods were proposed respectively inspired by the mass diffusion (MD) and heat conduction (HC) processes on networks. It has been pointed out that MD has high recommendation accuracy yet low diversity, while HC succeeds in seeking out novel or niche items but with relatively low accuracy. The accuracy-diversity dilemma is a long-term challenge in recommender systems. To solve this problem, we introduced a background temperature by adding a ground user who connects to all the items in the user-item bipartite network. Performing the HC algorithm on the network with ground user (GHC), it showed that the accuracy can be largely improved while keeping the diversity. Furthermore, we proposed a weighted form of the ground user (WGHC) by assigning some weights to the newly added links between the ground user and the items. By turning the weight as a free parameter, an optimal value subject to the highest accuracy is obtained. Experimental results on three benchmark data sets showed that the WGHC outperforms the state-of-the-art method MD for both accuracy and diversity.

  18. User Controllability in a Hybrid Recommender System

    Science.gov (United States)

    Parra Santander, Denis Alejandro

    2013-01-01

    Since the introduction of Tapestry in 1990, research on recommender systems has traditionally focused on the development of algorithms whose goal is to increase the accuracy of predicting users' taste based on historical data. In the last decade, this research has diversified, with "human factors" being one area that has received…

  19. On the Recommender System for University Library

    Science.gov (United States)

    Fu, Shunkai; Zhang, Yao; Seinminn

    2013-01-01

    Libraries are important to universities, and they have two primary features: readers as well as collections are highly professional. In this study, based on the experimental study with five millions of users' borrowing records, our discussion covers: (1) the necessity of recommender system for university libraries; (2) collaborative filtering (CF)…

  20. Mining Feedback in Ranking and Recommendation Systems

    Science.gov (United States)

    Zhuang, Ziming

    2009-01-01

    The amount of online information has grown exponentially over the past few decades, and users become more and more dependent on ranking and recommendation systems to address their information seeking needs. The advance in information technologies has enabled users to provide feedback on the utilities of the underlying ranking and recommendation…

  1. Evaluation of Recommender Systems for Technology-Enhanced Learning: Challenges and Possible Solutions

    NARCIS (Netherlands)

    Sandy, Heleau; Drachsler, Hendrik; Gillet, Dennis

    2009-01-01

    Heleou, S., Drachsler, H., & Gillet, D. (2009). Evaluation of Recommender Systems for Technology-Enhanced Learning: Challenges and Possible Solutions. 1st workshop on Context-aware Recommender Systems for Learning at the Alpine Rendez-Vous. November, 30-December, 3, 2009, Garmisch-Patenkirchen,

  2. A Dynamic Recommender System for Improved Web Usage Mining and CRM Using Swarm Intelligence.

    Science.gov (United States)

    Alphy, Anna; Prabakaran, S

    2015-01-01

    In modern days, to enrich e-business, the websites are personalized for each user by understanding their interests and behavior. The main challenges of online usage data are information overload and their dynamic nature. In this paper, to address these issues, a WebBluegillRecom-annealing dynamic recommender system that uses web usage mining techniques in tandem with software agents developed for providing dynamic recommendations to users that can be used for customizing a website is proposed. The proposed WebBluegillRecom-annealing dynamic recommender uses swarm intelligence from the foraging behavior of a bluegill fish. It overcomes the information overload by handling dynamic behaviors of users. Our dynamic recommender system was compared against traditional collaborative filtering systems. The results show that the proposed system has higher precision, coverage, F1 measure, and scalability than the traditional collaborative filtering systems. Moreover, the recommendations given by our system overcome the overspecialization problem by including variety in recommendations.

  3. Implicit function with natural behavior over entire domain

    International Nuclear Information System (INIS)

    Itoh, Taku; Saitoh, Ayumu; Kamitani, Atsushi; Nakamura, Hiroaki

    2012-01-01

    To generate a smooth implicit function that behaves naturally over an entire domain, a method to smoothly combine an implicit function f(x) with a global support function g(x) has been proposed. The proposed method can be applied to large scattered point data, since the implicit function f(x) is generated by a partition-of-unity-based method. The global support function g(x) is generated by a radial basis function-based method or by the least-squares method. To ensure a smooth combination of f(x) and g(x), an appropriate weight function is employed. In numerical experiments, the proposed method is applied to large point data. The results illustrate that the proposed method can generate a smooth implicit function F(x) with natural behavior over the entire domain. In addition, on the given points, the accuracy of F(x) is exactly the same as that of f(x). Furthermore, the computational cost for generation of F(x) is almost the same as that of f(x). (author)

  4. Explicit behavioral detection of visual changes develops without their implicit neurophysiological detectability

    Directory of Open Access Journals (Sweden)

    Pessi eLyyra

    2012-03-01

    Full Text Available Change blindness is a failure of explicitly detecting changes between consecutively presented images when separated, e.g., by a brief blank screen. There is a growing body of evidence of implicit detection of even explicitly undetectable changes, pointing to the possibility of the implicit change detection as a prerequisite for its explicit counterpart. We recorded event-related potentials (ERPs of the electroencephalography in adults during an oddball-variant of change blindness flicker paradigm. In this variant, rare pictures with a change were interspersed with frequent pictures with no change. In separate stimulus blocks, the blank screen between the change and no-change picture was either of 100 ms or 500 ms in duration. In both stimulus conditions the participants eventually explicitly detect the changed pictures, the blank screen of the longer duration only requiring in average 10 % longer exposure to the picture series until the ability emerged. However, during the change blindness, ERPs were displaced towards negative polarity at 200–260 ms after the stimulus onset (visual mismatch negativity only with the blank screens of the shorter ISI. Our finding of ‘implicit change blindness’ for pictorial material that, nevertheless, successfully prepares the visual system for explicit change detection suggests that implicit change detection may not be a necessary condition for explicit change detection and that they may recruit at least partially distinct memory mechanisms.

  5. [Explicit and implicit attitudes toward standard-Japanese and Osaka-dialect language use].

    Science.gov (United States)

    Watanabe, Takumi; Karasawa, Kaori

    2013-04-01

    This article examines the effects of language use on explicit and implicit attitudes. We employed the matched-guise technique to measure participants' impressions of standard-Japanese and Osaka-dialect speakers. Implicit attitudes were assessed by the Implicit Association Test (IAT). The Osaka-dialect speaker was evaluated as warmer than the standard-Japanese speaker, suggesting that explicit attitudes toward the Osaka dialect have changed positively. On the other hand, the results for the impression of intelligence were consistent with the previous literature that the standard-Japanese speaker was seen as more intelligent than the Osaka-dialect speaker. Compared with explicit attitudes, the analyses of implicit attitudes revealed that participants showed a consistent implicit bias favoring standard-Japanese language use. The changing processes and relationships of explicit and implicit attitudes were discussed.

  6. A Hybrid Approach using Collaborative filtering and Content based Filtering for Recommender System

    Science.gov (United States)

    Geetha, G.; Safa, M.; Fancy, C.; Saranya, D.

    2018-04-01

    In today’s digital world, it has become an irksome task to find the content of one's liking in an endless variety of content that are being consumed like books, videos, articles, movies, etc. On the other hand there has been an emerging growth among the digital content providers who want to engage as many users on their service as possible for the maximum time. This gave birth to the recommender system comes wherein the content providers recommend users the content according to the users’ taste and liking. In this paper we have proposed a movie recommendation system. A movie recommendation is important in our social life due to its features such as suggesting a set of movies to users based on their interest, or the popularities of the movies. In this paper we are proposing a movie recommendation system that has the ability to recommend movies to a new user as well as the other existing users. It mines movie databases to collect all the important information, such as, popularity and attractiveness, which are required for recommendation. We use content-based and collaborative filtering and also hybrid filtering, which is a combination of the results of these two techniques, to construct a system that provides more precise recommendations concerning movies.

  7. Implicit Recognition Based on Lateralized Perceptual Fluency

    OpenAIRE

    Vargas, Iliana M.; Voss, Joel L.; Paller, Ken A.

    2012-01-01

    In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this “implicit recognition” results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention enc...

  8. Attentional load and implicit sequence learning.

    Science.gov (United States)

    Shanks, David R; Rowland, Lee A; Ranger, Mandeep S

    2005-06-01

    A widely employed conceptualization of implicit learning hypothesizes that it makes minimal demands on attentional resources. This conjecture was investigated by comparing learning under single-task and dual-task conditions in the sequential reaction time (SRT) task. Participants learned probabilistic sequences, with dual-task participants additionally having to perform a counting task using stimuli that were targets in the SRT display. Both groups were then tested for sequence knowledge under single-task (Experiments 1 and 2) or dual-task (Experiment 3) conditions. Participants also completed a free generation task (Experiments 2 and 3) under inclusion or exclusion conditions to determine if sequence knowledge was conscious or unconscious in terms of its access to intentional control. The experiments revealed that the secondary task impaired sequence learning and that sequence knowledge was consciously accessible. These findings disconfirm both the notion that implicit learning is able to proceed normally under conditions of divided attention, and that the acquired knowledge is inaccessible to consciousness. A unitary framework for conceptualizing implicit and explicit learning is proposed.

  9. A New Profile Learning Model for Recommendation System based on Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Shereen H. Ali

    2016-03-01

    Full Text Available Recommender systems (RSs have been used to successfully address the information overload problem by providing personalized and targeted recommendations to the end users. RSs are software tools and techniques providing suggestions for items to be of use to a user, hence, they typically apply techniques and methodologies from Data Mining. The main contribution of this paper is to introduce a new user profile learning model to promote the recommendation accuracy of vertical recommendation systems. The proposed profile learning model employs the vertical classifier that has been used in multi classification module of the Intelligent Adaptive Vertical Recommendation (IAVR system to discover the user’s area of interest, and then build the user’s profile accordingly. Experimental results have proven the effectiveness of the proposed profile learning model, which accordingly will promote the recommendation accuracy.

  10. Multithreaded implicitly dealiased convolutions

    Science.gov (United States)

    Roberts, Malcolm; Bowman, John C.

    2018-03-01

    Implicit dealiasing is a method for computing in-place linear convolutions via fast Fourier transforms that decouples work memory from input data. It offers easier memory management and, for long one-dimensional input sequences, greater efficiency than conventional zero-padding. Furthermore, for convolutions of multidimensional data, the segregation of data and work buffers can be exploited to reduce memory usage and execution time significantly. This is accomplished by processing and discarding data as it is generated, allowing work memory to be reused, for greater data locality and performance. A multithreaded implementation of implicit dealiasing that accepts an arbitrary number of input and output vectors and a general multiplication operator is presented, along with an improved one-dimensional Hermitian convolution that avoids the loop dependency inherent in previous work. An alternate data format that can accommodate a Nyquist mode and enhance cache efficiency is also proposed.

  11. Implicit Methods for the Magnetohydrodynamic Description of Magnetically Confined Plasmas

    International Nuclear Information System (INIS)

    Jardin, S.C.

    2010-01-01

    Implicit algorithms are essential for predicting the slow growth and saturation of global instabilities in today's magnetically confined fusion plasma experiments. Present day algorithms for obtaining implicit solutions to the magnetohydrodynamic (MHD) equations for highly magnetized plasma have their roots in algorithms used in the 1960s and 1970s. However, today's computers and modern linear and non-linear solver techniques make practical much more comprehensive implicit algorithms than were previously possible. Combining these advanced implicit algorithms with highly accurate spatial representations of the vector fields describing the plasma flow and magnetic fields and with improved methods of calculating anisotropic thermal conduction now makes possible simulations of fusion experiments using realistic values of plasma parameters and actual configuration geometry.

  12. Assessment of implicit sexual associations in non-incarcerated pedophiles

    NARCIS (Netherlands)

    Leeuwen, M.L. van; Baaren, R.B. van; Chakhssi, F.; Loonen, M.G.M.; Lippman, Maarten; Dijksterhuis, A.J.

    2013-01-01

    Offences committed by pedophiles are crimes that evoke serious public concern and outrage. Although recent research using implicit measures has shown promise in detecting deviant sexual associations, the discriminatory and predictive quality of implicit tasks has not yet surpassed traditional

  13. Intact memory for implicit contextual information in Korsakoff's amnesia

    NARCIS (Netherlands)

    Oudman, Erik; Van der Stigchel, Stefan; Wester, Arie J.; Kessels, Roy P. C.; Postma, Albert

    Implicit contextual learning is the ability to acquire contextual information from our surroundings without conscious awareness. Such contextual information facilitates the localization of objects in space. In a typical implicit contextual learning paradigm, subjects need to find a target among a

  14. Intact memory for implicit contextual information in Korsakoff's amnesia

    NARCIS (Netherlands)

    Oudman, E.; Stigchel, S. van der; Wester, A.J.; Kessels, R.P.C.; Postma, A.

    2011-01-01

    Implicit contextual learning is the ability to acquire contextual information from our surroundings without conscious awareness. Such contextual information facilitates the localization of objects in space. In a typical implicit contextual learning paradigm, subjects need to find a target among a

  15. Kernel based collaborative recommender system for e-purchasing

    Indian Academy of Sciences (India)

    proposed in order to overcome the traditional problems of CRS. ... known method for matrix factorization that provides the lowest rank ..... Adomavicius G, Tuzhilin A 2005 Toward the next generation of recommender systems: A survey of.

  16. Implicit and Explicit Memory for Affective Passages in Temporal Lobectomy Patients

    Science.gov (United States)

    Burton, Leslie A.; Rabin, Laura; Vardy, Susan Bernstein; Frohlich, Jonathan; Porter, Gwinne Wyatt; Dimitri, Diana; Cofer, Lucas; Labar, Douglas

    2008-01-01

    Eighteen temporal lobectomy patients (9 left, LTL; 9 right, RTL) were administered four verbal tasks, an Affective Implicit Task, a Neutral Implicit Task, an Affective Explicit Task, and a Neutral Explicit Task. For the Affective and Neutral Implicit Tasks, participants were timed while reading aloud passages with affective or neutral content,…

  17. Studies of implicit and explicit solution techniques in transient thermal analysis of structures

    International Nuclear Information System (INIS)

    Adelman, H.M.; Haftka, R.T.; Robinson, J.C.

    1982-08-01

    Studies aimed at an increase in the efficiency of calculating transient temperature fields in complex aerospace vehicle structures are reported. The advantages and disadvantages of explicit and implicit algorithms are discussed and a promising set of implicit algorithms with variable time steps, known as GEARIB, is described. Test problems, used for evaluating and comparing various algorithms, are discussed and finite element models of the configurations are described. These problems include a coarse model of the Space Shuttle wing, an insulated frame test article, a metallic panel for a thermal protection system, and detailed models of sections of the Space Shuttle wing. Results generally indicate a preference for implicit over explicit algorithms for transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures). The effects on algorithm performance of different models of an insulated cylinder are demonstrated. The stiffness of the problem is highly sensitive to modeling details and careful modeling can reduce the stiffness of the equations to the extent that explicit methods may become the best choice. Preliminary applications of a mixed implicit-explicit algorithm and operator splitting techniques for speeding up the solution of the algebraic equations are also described

  18. Studies of implicit and explicit solution techniques in transient thermal analysis of structures

    Science.gov (United States)

    Adelman, H. M.; Haftka, R. T.; Robinson, J. C.

    1982-01-01

    Studies aimed at an increase in the efficiency of calculating transient temperature fields in complex aerospace vehicle structures are reported. The advantages and disadvantages of explicit and implicit algorithms are discussed and a promising set of implicit algorithms with variable time steps, known as GEARIB, is described. Test problems, used for evaluating and comparing various algorithms, are discussed and finite element models of the configurations are described. These problems include a coarse model of the Space Shuttle wing, an insulated frame tst article, a metallic panel for a thermal protection system, and detailed models of sections of the Space Shuttle wing. Results generally indicate a preference for implicit over explicit algorithms for transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures). The effects on algorithm performance of different models of an insulated cylinder are demonstrated. The stiffness of the problem is highly sensitive to modeling details and careful modeling can reduce the stiffness of the equations to the extent that explicit methods may become the best choice. Preliminary applications of a mixed implicit-explicit algorithm and operator splitting techniques for speeding up the solution of the algebraic equations are also described.

  19. Achieving Optimal Privacy in Trust-Aware Social Recommender Systems

    Science.gov (United States)

    Dokoohaki, Nima; Kaleli, Cihan; Polat, Huseyin; Matskin, Mihhail

    Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers proposed for utilization of interpersonal trust between users, to alleviate many of these crucial shortcomings. Till now, attention has been mainly paid to strong points about trust-aware recommenders such as alleviating profile sparsity or calculation cost efficiency, while least attention has been paid on investigating the notion of privacy surrounding the disclosure of individual ratings and most importantly protection of trust computation across social networks forming the backbone of these systems. To contribute to addressing problem of privacy in trust-aware recommenders, within this paper, first we introduce a framework for enabling privacy-preserving trust-aware recommendation generation. While trust mechanism aims at elevating recommender's accuracy, to preserve privacy, accuracy of the system needs to be decreased. Since within this context, privacy and accuracy are conflicting goals we show that a Pareto set can be found as an optimal setting for both privacy-preserving and trust-enabling mechanisms. We show that this Pareto set, when used as the configuration for measuring the accuracy of base collaborative filtering engine, yields an optimized tradeoff between conflicting goals of privacy and accuracy. We prove this concept along with applicability of our framework by experimenting with accuracy and privacy factors, and we show through experiment how such optimal set can be inferred.

  20. Preference Elicitation and Negotiation in a Group Recommender System

    OpenAIRE

    Álvarez Márquez , Jesús ,; Ziegler , Jurgen

    2015-01-01

    International audience; We present a novel approach to group recommender systems that better takes into account the social interaction in a group when formulating, discussing and negotiating the features of the item to be jointly selected. Our approach provides discussion support in a collaborative preference elicitation and negotiation process. Individual preferences are continuously aggregated and immediate feedback of the resulting recommendations is provided. We also support the last stag...