Improved collaborative filtering algorithm based
on heat conduction

doi:10.1007/s11704-009-0050-2

Front. Comput. Sci.

2009, Vol. 3

Issue (3) : 417-420 https://doi.org/10.1007/s11704-009-0050-2

Research articles

Improved collaborative filtering algorithm based on heat conduction

Qiang GUO ¹, Jianguo LIU ², Binghong WANG ³,

1.Business School, University of Shanghai for Science and Technology, Shanghai 200093, China；Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Switzerland; 2.Research Center of Complex Systems Science, Shanghai University of Science and Technology, Shanghai 200093, China；Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China；Department of Physics, University of Fribourg, Chemin du Musée 3, CH-1700, Switzerland; 3.Research Center of Complex Systems Science, Shanghai University of Science and Technology, Shanghai 200093, China；Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China;

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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.

Keywords recommendation algorithm collaborative filtering heat conduction

Issue Date: 05 September 2009

Cite this article:

Qiang GUO,Binghong WANG,Jianguo LIU. Improved collaborative filtering algorithm based on heat conduction[J]. Front. Comput. Sci., 2009, 3(3): 417-420.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-009-0050-2
https://academic.hep.com.cn/fcs/EN/Y2009/V3/I3/417

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