Volume 82, Number 5, June 2008
|Number of page(s)||5|
|Section||Interdisciplinary Physics and Related Areas of Science and Technology|
|Published online||30 May 2008|
Information filtering via self-consistent refinement
Department of Physics, University of Fribourg - Chemin du Muse 3, 1700 Fribourg, Switzerland
2 Department of Physics and Centre for Computational Science and Engineering, National University of Singapore - Singapore 117542, Republic of Singapore
3 Department of Modern Physics, University of Science and Technology of China - Hefei 230026, PRC
4 Information Economy and Internet Research Laboratory, University of Electronic Science and Technology of China - Chengdu 610054, PRC
Corresponding author: email@example.com
Accepted: 15 April 2008
Recommender systems are significant to help people deal with the world of information explosion and overload. In this letter, we develop a general framework named self-consistent refinement and implement it by embedding two representative recommendation algorithms: similarity-based and spectrum-based methods. Numerical simulations on a benchmark data set demonstrate that the present method converges fast and can provide quite better performance than the standard methods.
PACS: 89.75.-k – Complex systems / 89.20.Hh – World Wide Web, Internet / 89.65.Gh – Economics; econophysics, financial markets, business and management
© EPLA, 2008
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