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A Collaborative Filtering Algorithm Based on Attribution Theory

  • Mao DeLeiEmail author
  • Tang Yan
  • Liu Bing
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10942)

Abstract

The Collaborative filtering algorithm predicts the user’s preference for the project to complete a recommendation by analyzing the user preference data, and usually takes the user’s rating as the user preference data. However, there is a bias between user’s preference and user’s score of the real scene, so the user’s rating as user preference can lead to lower recommendation accuracy. For this problem, this paper proposes a user preference extraction method based on attribution theory, calculates user preferences by analyzing user rating behavior. Then, combining preference similarity and rate similarity, making up the bias between user rating and user preference in collaborative filtering algorithm. Experimental verification on universal Dataset Movies lens-1m results shows that the algorithm is preferable to the existing collaborative filtering algorithm.

Keywords

Attribution theory User preference Collaborative filtering Recommender system 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Southwest UniversityChongqingChina
  2. 2.Dazhou Vocational and Technical CollegeDazhouChina

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