Issue
EPL
Volume 82, Number 5, June 2008
Article Number 58007
Number of page(s) 5
Section Interdisciplinary Physics and Related Areas of Science and Technology
DOI http://dx.doi.org/10.1209/0295-5075/82/58007
Published online 30 May 2008
EPL, 82 (2008) 58007
DOI: 10.1209/0295-5075/82/58007

Information filtering via self-consistent refinement

Jie Ren1, 2, Tao Zhou1, 3, 4 and Yi-Cheng Zhang1, 4

1  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

zhutou@ustc.edu

received 29 February 2008; accepted in final form 15 April 2008; published June 2008
published online 30 May 2008

Abstract
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