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

Empirical study on clique-degree distribution of networks

Xiao, Wei-Ke ; Ren, Jie ; Qi, Feng ; Song, Zhi-Wei ; Zhu, Meng-Xiao ; Yang, Hong-Feng ; Jin, Hui-Yu ; Wang, Bing-Hong ; Zhou, Tao

In: Physical Review E, 2007, vol. 76, no. 3, p. 037102

The community structure and motif-modular-network hierarchy are of great importance for understanding the relationship between structures and functions. We investigate the distribution of clique degrees, which are an extension of degree and can be used to measure the density of cliques in networks. Empirical studies indicate the extensive existence of power-law clique-degree distributions in...

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...

Université de Fribourg

Randomness enhances cooperation: A resonance-type phenomenon in evolutionary games

Ren, Jie ; Wang, Wen-Xu ; Qi, Feng

In: Physical Review E, 2007, vol. 75, p. 045101

We investigate the effect of randomness in both relationships and decisions on the evolution of cooperation. Simulation results show, in such randomness' presence, the system evolves more frequently to a cooperative state than in its absence. Specifically, there is an optimal amount of randomness, which can induce the highest level of cooperation. The mechanism of randomness promoting cooperation...