Université de Fribourg

Information filtering in sparse online systems: recommendation via semi-local diffusion

Zeng, Wei ; Zeng, An ; Shang, Ming-Sheng ; Zhang, Yi-Cheng

In: PLoS ONE, 2013, vol. 8, no. 11, p. e79354

With the rapid growth of the Internet and overwhelming amount of information and choices that people are confronted with, recommender systems have been developed to effectively support users’ decision-making process in the online systems. However, many recommendation algorithms suffer from the data sparsity problem, i.e. the user-object bipartite networks are so sparse that algorithms cannot...

Université de Fribourg

Membership in social networks and the application in information filtering

Zeng, Wei ; Zeng, An ; Shang, Ming-Sheng ; Zhang, Yi-Cheng

In: The European Physical Journal B, 2013, vol. 86, no. 9, p. 1-7

During the past few years, users’ membership in the online system (i.e. the social groups that online users joined) were widely investigated. Most of these works focus on the detection, formulation and growth of online communities. In this paper, we study users’ membership in a coupled system which contains user-group and user- object bipartite networks. By linking users’ membership...

Université de Fribourg

Preference of online users and personalized recommendations

Guan, Yuan ; Zhao, Dandan ; Zeng, An ; Shang, Ming-Sheng

In: Physica A: Statistical Mechanics and its Applications, 2013, p. -

In a recent work [T. Zhou, Z. Kuscsik, J.-G. Liu, M. Medo, J.R. Wakeling, Y.-C. Zhang, Proc. Natl. Acad. Sci. 107 (2010) 4511], a personalized recommendation algorithm with high performance in both accuracy and diversity is proposed. This method is based on the hybridization of two single algorithms called probability spreading and heat conduction, which respectively are inclined to recommend...

Université de Fribourg

Identifying influential nodes in complex networks

Lü, Linyuan ; Shang, Ming-Sheng ; Zhang, Yi-Cheng ; Zhou, Tao

In: Physica A: Statistical Mechanics and its Applications, 2011, vol. 391, no. 4, p. 1777–1787

Identifying influential nodes that lead to faster and wider spreading in complex networks is of theoretical and practical significance. The degree centrality method is very simple but of little relevance. Global metrics such as betweenness centrality and closeness centrality can better identify influential nodes, but are incapable to be applied in large-scale networks due to the computational...

Université de Fribourg

Similarity-based classification in partially labeled networks

Zhang, Qian-Ming ; Shang, Ming-Sheng ; Lü, Linyuan

In: International Journal of Modern Physics C, 2010, vol. 21, no. 6, p. 813-824

Two main difficulties in the problem of classification in partially labeled networks are the sparsity of the known labeled nodes and inconsistency of label information. To address these two difficulties, we propose a similarity-based method, where the basic assumption is that two nodes are more likely to be categorized into the same class if they are more similar. In this paper, we introduce ten...

Université de Fribourg

Empirical comparison of local structural similarity indices for collaborative-filtering-based recommender systems

Zhang, Qian-Ming ; Shang, Ming-Sheng ; Zeng, Wei ; Chen, Yong ; Lü, Linyuan

In: Physics Procedia, 2010, vol. 3, no. 5, p. 1887-1896

Collaborative filtering is one of the most successful recommendation techniques, which can effectively predict the possible future likes of users based on their past preferences. The key problem of this method is how to define the similarity between users. A standard approach is using the correlation between the ratings that two users give to a set of objects, such as Cosine index and Pearson...

Université de Fribourg

Empirical analysis of web-based user-object bipartite networks

Shang, Ming-Sheng ; Lü, Linyuan ; Zhang, Yi-Cheng ; Zhou, Tao

In: Europhysics Letters, 2010, vol. 90, no. 4, p. 48006

Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com (http://audioscrobbler.com/) and del.icio.us (http://del.icio.us/), where users are connected with music groups and bookmarks, respectively. The degree...

Université de Fribourg

Interest-driven model for human dynamics

Shang, Ming-Sheng ; Chen, Guan-Xiong ; Dai, Shuang-Xing ; Wang, Bing-Hong ; Zhou, Tao

In: Chinese Physics Letters, 2010, vol. 27, no. 4, p. 048701

Empirical observations indicate that the interevent time distribution of human actions exhibits heavy-tailed features. The queuing model based on task priorities is to some extent successful in explaining the origin of such heavy tails, however, it cannot explain all the temporal statistics of human behavior especially for the daily entertainments. We propose an interest-driven model, which can...

Université de Fribourg

Relevance is more significant than correlation: Information filtering on sparse data

Shang, Ming-Sheng ; Lü, Linyuan ; Zeng, Wei ; Zhang, Yi-Cheng ; Zhou, Tao

In: Europhysics Letters, 2009, vol. 88, no. 6, p. 68008

In some recommender systems where users can vote objects by ratings, the similarity between users can be quantified by a benchmark index, namely the Pearson correlation coefficient, which reflects the rating correlations. Another alternative way is to calculate the similarity based solely on the relevance information, namely whether a user has voted an object. The former one uses more information...