Université de Fribourg

Identifying online user reputation of user–object bipartite networks

Liu, Xiao-Lu ; Liu, Jian-Guo ; Yang, Kai ; Guo, Qiang ; Han, Jing-Ti

In: Physica A: Statistical Mechanics and its Applications, 2017, vol. 467, p. 508–516

Identifying online user reputation based on the rating information of the user–object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part...

Université de Fribourg

Evolution properties of online user preference diversity

Guo, Qiang ; Ji, Lei ; Liu, Jian-Guo ; Han, Jingti

In: Physica A: Statistical Mechanics and its Applications, 2017, vol. 468, p. 698–713

Detecting the evolution properties of online user preference diversity is of significance for deeply understanding online collective behaviors. In this paper, we empirically explore the evolution patterns of online user rating preference, where the preference diversity is measured by the variation coefficient of the user rating sequence. The statistical results for four real systems show...

Université de Fribourg

Evolution characteristics of the network core in the facebook

Liu, Jian-Guo ; Ren, Zhuo-Ming ; Guo, Qiang ; Chen, Duan-Bing

In: PLoS ONE, 2014, vol. 9, no. 8, p. e104028

Statistical properties of the static networks have been extensively studied. However, online social networks are evolving dynamically, understanding the evolving characteristics of the core is one of major concerns in online social networks. In this paper, we empirically investigate the evolving characteristics of the Facebook core. Firstly, we separate the Facebook-link(FL) and Facebook-wall(FW)...

Université de Fribourg

Heat conduction information filtering via local information of bipartite networks

Guo, Qiang ; Leng, R. ; Shi, K. ; Liu, J.G.

In: The European Physical Journal B - Condensed Matter and Complex Systems, 2012, vol. 85, no. 8, p. 286

Information filtering based on structure properties of user-object bipartite networks is of both theoretical interest and practical significance in modern science. In this paper, we empirically investigate the framework of heat-conduction-based (HC) information filtering [Y.-C. Zhang et al., Phys. Rev. Lett. 99, 154301 (2007)] in terms of the local node similarity. We compare nine well-known...

Université de Fribourg

Information filtering via weighted heat conduction algorithm

Liu, Jian-Guo ; Guo, Qiang ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2011, p. -

In this paper, by taking into account effects of the user and object correlations on a heat conduction (HC) algorithm, a weighted heat conduction (WHC) algorithm is presented. We argue that the edge weight of the user–object bipartite network should be embedded into the HC algorithm to measure the object similarity. The numerical results indicate that both the accuracy and diversity could be...

Université de Fribourg

Degree correlation of bipartite network on personalized recommendation

Liu, Jian-Guo ; Zhou, Tao ; Zhang, Yi-Cheng ; Guo, Qiang

In: International Journal of Modern Physics C, 2010, vol. 21, no. 1, p. 137-147

In this paper, the statistical property, namely degree correlation between users and objects, is taken into account and be embedded into the similarity index of collaborative filtering (CF) algorithm to improve the algorithmic performance. The numerical simulation on a benchmark data set shows that the algorithmic accuracy of the presented algorithm, measured by the average ranking score, is...

Université de Fribourg

Improved collaborative filtering algorithm via information transformation

Liu, Jian-Guo ; Wang, Bing-Hong ; Guo, Qiang

In: International Journal of Modern Physics C, 2009, vol. 20, no. 2, p. 285-293

In this paper, we propose a spreading activation approach for collaborative filtering (SA-CF). By using the opinion spreading process, the similarity between any users can be obtained. The algorithm has remarkably higher accuracy than the standard collaborative filtering using the Pearson correlation. Furthermore, we introduce a free parameter β to regulate the contributions of objects to...

Université de Fribourg

Effects of user's tastes on personalized recommendation

Liu, Jian-Guo ; Zhou, Tao ; Wang, Bing-Hong ; Zhang, Yi-Cheng ; Guo, Qiang

In: International Journal of Modern Physics C, 2009, vol. 20, no. 12, p. 1925-1932

In this paper, based on a weighted projection of the user-object bipartite network, we study the effects of user tastes on the mass-diffusion-based personalized recommendation algorithm, where a user's tastes or interests are defined by the average degree of the objects he has collected. We argue that the initial recommendation power located on the objects should be determined by both of their...

Université de Fribourg

Structural effects on synchronizability of scale-free networks

Liu, Jian-Guo ; Zhou, Tao ; Guo, Qiang ; Wang, Bing-Hong

In: International Journal of Modern Physics C, 2008, vol. 19, no. 9, p. 1359 - 1366

In this paper, we numerically investigate the structural characteristics that affect the synchronizability of coupled identical oscillators on scale-free networks. By using the edge-exchange method, we can change the network structure with degree sequence fixed. An optimal algorithm, namely Tabu Search, is applied, respectively, to enhance and weaken the synchronizability. The numerical results...

Université de Fribourg

Opinion spreading with mobility on scale-free networks

Guo, Qiang ; Liu, Jian-Guo ; Wang, Bing-Hong ; Zhou, Tao ; Chen, Xing-Wen ; Yao, Yu-Hua

In: Chinese Physics Letters, 2008, vol. 25, no. 2, p. 773-775

A continuum opinion dynamic model is presented based on two rules. The first one considers the mobilities of the individuals, the second one supposes that the individuals update their opinions independently. The results of the model indicate that the bounded confidence ∈c, separating consensus and incoherent states, of a scale-free network is much smaller than the one of a...