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Personality prediction has broad prospects of application in real life. It can be accomplished by analyzing massive and variant data in social networks, which conveys one's personal traits through user generated contents, user's social relationships and behaviors. However, it is difficult to design an effective feature representation from such complex data to predict user's personality as well as...
Music auto-tagging has been an active research topic as it learns the relationship between the content of audio tracks and semantic tags such that users can query by both tags and audio segments without being troubled by the cold start problem. In this paper, we propose a new trigger-based context model to refine the existing content model based auto-tagging systems. The trigger based context model...
Over the last decade, advances in high performance computing and remote sensing have produced a vast amount of spatio-temporal data. One area that this data explosion is most prevalent is climate science. With this in mind, there is an increasing need to characterize large spatio-temporal datasets. One such characterization is to find periods of time that exhibit the same spatio-temporal pattern....
In this paper, we focus on automatic quality assessment for intelligent essay grading. Our devised system grades essays without depending upon completely overlapping essays in training data. This increases the scope of devised system due to list dependency on highly topic focused labeled data for automatic essay grading. Instead of depending upon direct topic specific matching w.r.t., training data,...
Mining community on the basis of hidden relationships present between the entities is important from academic recommendation point of view. Previous approaches mined research community by using network connectivity or by ignoring semantics-based intrinsic structure of the words and author's relationships present between the conferences. In this paper, we propose a novel Venue-Author-Topic (VAT) approach...
The “information goal” underlying user activity on the web is an important latent parameter. Its determination can help in a wide variety of tasks ranging from improving the quality of a search engine's results to design and evaluation of web sites. The problem of determining user information goals is exacerbated in media-rich websites. The complexity lies in the fact that the semantics as well as...
Assessment is an important component of learning and it also noted that many academic examination make heavy used of short answers. This assessment can be a tedious task. However, there are not many computer-based assessment tools due to limitations in computerized marking technology. Our research attempts to address this limitation by introducing a technique to evaluate short free text answer. It...
In this paper, we have postulated the problem of using discrete speech utterances to annotate an image as that of disambiguation across multiple N-best lists. Our solution is based on the Maximum Entropy approach and uses correlations between tags in an existing corpus of images to set up the constrains of the corresponding constrained optimization problem. Our experiments suggest that the proposed...
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