Université de Fribourg

Recommendation model based on opinion diffusion

Zhang, Yi-Cheng ; Medo, Matúš ; Ren, Jie ; Zhou, Tao ; Li, T. ; Yang, F.

In: Europhysics Letters, 2007, vol. 80, no. 6, p. 68003

Information overload in the modern society calls for highly efficient recommendation algorithms. In this letter we present a novel diffusion-based recommendation model, with users' ratings built into a transition matrix. To speed up computation we introduce a Green function method. The numerical tests on a benchmark database show that our prediction is superior to the standard recommendation...

Université de Fribourg

Information filtering via self-consistent refinement

Ren, Jie ; Zhou, Tao ; Zhang, Yi-Cheng

In: Europhysics Letters, 2008, vol. 82, no. 5, p. 58007

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...

Université de Fribourg

Bipartite network projection and personal recommendation

Zhou, Tao ; Ren, Jie ; Medo, Matúš ; Zhang, Yi-Cheng

In: Physical Review E, 2007, vol. 76, no. 4, p. 046115

One-mode projecting is extensively used to compress bipartite networks. Since one-mode projection is always less informative than the bipartite representation, a proper weighting method is required to better retain the original information. In this article, inspired by the network-based resource-allocation dynamics, we raise a weighting method which can be directly applied in extracting the...