Temporal rating habits: a valuable tool for rating discrimination
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation（2011）
摘要
In this paper, we describe the experiments conducted by the Information Retrieval Group at the Universidad Autónoma de Madrid (Spain) to tackle the Identifying Ratings (track 2) task of the CAMRa 2011 Challenge. The experiments performed include time-frequency probabilistic strategies, heuristic collaborative filtering (CF) and a model-based CF approach. Results show that probabilistic classifiers based on temporal behavior of users have better performance than traditional recommendation-based strategies, thus reflecting that temporal information is a valuable source for the identification or discrimination of user ratings.
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关键词
temporal information,temporal behavior,information retrieval group,heuristic collaborative,rating discrimination,temporal rating habit,probabilistic classifier,time-frequency probabilistic strategy,identifying ratings,better performance,universidad aut,model-based cf approach,valuable tool,recommender system,collaborative filtering,time frequency,information retrieval
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