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Improved collaborative filtering algorithm based on heat conduction

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Abstract

In this paper, we present an improved collaborative filtering (ICF) algorithm by using the heat diffusion process to generate the user correlation. This algorithm has remarkably higher accuracy than the standard collaborative filtering (CF) using Pearson correlation. Furthermore, we introduce a free parameter β to regulate the contributions of objects to user correlation. The numerical simulation results indicate that decreasing the influence of popular objects can further improve the algorithmic accuracy and diversity.

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Authors and Affiliations

  1. Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Qiang Guo

  2. Research Center of Complex Systems Science, Shanghai University of Science and Technology, Shanghai, 200093, China

    Jianguo Liu & Binghong Wang

  3. Department of Modern Physics, University of Science and Technology of China, Hefei, 230026, China

    Jianguo Liu & Binghong Wang

  4. Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Fribourg, Switzerland

    Qiang Guo & Jianguo Liu

Authors
  1. Qiang Guo
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  2. Jianguo Liu
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  3. Binghong Wang
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Correspondence to Jianguo Liu.

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Guo, Q., Liu, J. & Wang, B. Improved collaborative filtering algorithm based on heat conduction. Front. Comput. Sci. China 3, 417–420 (2009). https://doi.org/10.1007/s11704-009-0050-2

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  • DOI: https://doi.org/10.1007/s11704-009-0050-2

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