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Collaborative Filtering Recommendation Algorithm Based on User Acceptable Rating Radius

In: Liss 2013

Author

Listed:
  • Yue Huang

    (University of Science and Technology Beijing)

  • Xuedong Gao

    (University of Science and Technology Beijing)

  • Shujuan Gu

    (University of Science and Technology Beijing)

Abstract

Collaborative Filtering (CF) is the most widely applied technique in recommender systems. The key of CF algorithms lies in user similarity calculation. When calculating similarity of two users, traditional CF algorithms put a high value on absolute ratings of common rated items while ignoring the relative rating level difference to the same items. To obtain more precise user preference of different users, a CF-based recommendation algorithm based on user acceptable rating radius is proposed. Experimental results of recommendation on four MovieLens data sets with different scales demonstrate that our method distinguishes users effectively and outperforms traditional methods with respect to recommendation accuracy.

Suggested Citation

  • Yue Huang & Xuedong Gao & Shujuan Gu, 2015. "Collaborative Filtering Recommendation Algorithm Based on User Acceptable Rating Radius," Springer Books, in: Runtong Zhang & Zhenji Zhang & Kecheng Liu & Juliang Zhang (ed.), Liss 2013, pages 141-146, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-40660-7_20
    DOI: 10.1007/978-3-642-40660-7_20
    as

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