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Communication Dans Un Congrès Année : 2015

Context-Awareness and Viewer Behavior Prediction in Social-TV Recommender Systems: Survey and Challenges

Résumé

This paper surveys the landscape of actual personalized TV recommender systems, and introduces challenges on context-awareness and viewer behavior prediction applied to social TV-recommender systems. Real data related to the viewers behaviors and the social context have been picked up in real-time through a social TV platform. We highlighted the future benefits of analyzing viewer behavior and exploiting the social influence on viewers’s preferences to improve recommendation in respect with TV contents’ change.
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Dates et versions

hal-03213975 , version 1 (30-04-2021)

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Meriam Bambia, Rim Faiz, Mohand Boughanem. Context-Awareness and Viewer Behavior Prediction in Social-TV Recommender Systems: Survey and Challenges. 19th East-European Conference on Advances in Databases and Information Systems (ADBIS 2015), LIAS/ISAE-ENSMA - Laboratory of Computer Science and Automatic Control for Systems, Sep 2015, Poitiers, France. pp.52--59, ⟨10.1007/978-3-319-23201-0_7⟩. ⟨hal-03213975⟩
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