Information filtering based on transferring similarity

Sun, Duo, Zhou, Tao, Liu, Jianguo, Liu, Run-Ran, Jia, Chun-Xiao and Wang, Bing-Hong (2009) Information filtering based on transferring similarity. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), 80 (1). 017101.


In this Brief Report, we propose an index of user similarity, namely, the transferring similarity, which involves all high-order similarities between users. Accordingly, we design a modified collaborative filtering algorithm, which provides remarkably higher accurate predictions than the standard collaborative filtering. More interestingly, we find that the algorithmic performance will approach its optimal value when the parameter, contained in the definition of transferring similarity, gets close to its critical value, before which the series expansion of transferring similarity is convergent and after which it is divergent. Our study is complementary to the one reported in [ E. A. Leicht, P. Holme and M. E. J. Newman Phys. Rev. E 73 026120 (2006)], and is relevant to the missing link prediction problem.

Item Type: Article
Keywords: Data Analysis; Statistics and Probability; Physics and Society
Subject(s): Complexity
Centre: CABDyN Complexity Centre
Date Deposited: 11 Feb 2012 21:59
Last Modified: 23 Oct 2015 14:07

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