A New Similarity Measure-Based Collaborative Filtering Approach for Recommender Systems

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Conference Proceeding
Advances in Intelligent Systems and Computing, 2014, 277 pp. 443 - 452
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Collaborative filtering (CF) is the most popular recommendation approach in personalization techniques but still suffers from poor recommendation accuracy. This study incorporates fuzzy set technique and user-relevant analysis to improve the CF approach. It proposes an innovative fuzzy similarity measure (FSM) and user-relevant aggregation (URA) on recommendation approach. Experiments demonstrate that the FSM-URA approach significantly improves the prediction accuracy comparing to the existing recommendation approaches. © Springer-Verlag Berlin Heidelberg 2014.
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