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Université de Fribourg

An item-oriented recommendation algorithm on cold-start problem

Qiu, Tian ; Chen, Guang ; Zhang, Zi-Ke ; Zhou, Tao

In: EPL - Europhysics Letters, 2011, vol. 95, no. 5, p. 58003

Based on a hybrid algorithm incorporating the heat conduction and probability spreading processes (Proc. Natl. Acad. Sci. U.S.A., 107 (2010) 4511), in this letter, we propose an improved method by introducing an item-oriented function, focusing on solving the dilemma of the recommendation accuracy between the cold and popular items. Differently from previous works, the present algorithm does not...

Université de Fribourg

Heterogeneity, quality, and reputation in an adaptive recommendation model

Cimini, Giulio ; Medo, Matúš ; Zhou, Tao ; Wei, Dong ; Zhang, Yi-Cheng

In: The European Physical Journal B - Condensed Matter and Complex Systems, 2011, vol. 80, no. 2, p. 201-208

Recommender systems help people cope with the problem of information overload. A recently proposed adaptive news recommender model [M. Medo, Y.-C. Zhang, T. Zhou, Europhys. Lett. 88, 38005 (2009)] is based on epidemic-like spreading of news in a social network. By means of agent-based simulations we study a “good get richer” feature of the model and determine which attributes are necessary...

Université de Fribourg

Emergence of scale-free leadership structure in social recommender systems

Zhou, Tao ; Medo, Matúš ; Cimini, Giulio ; Zhang, Zi-Ke ; Zhang, Yi-Cheng

In: PLoS ONE, 2011, vol. 6, no. 7, p. e20648

The study of the organization of social networks is important for the understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this...

Université de Fribourg

Effective mechanism for social recommendation of news

Wei, Dong ; Zhou, Tao ; Cimini, Giulio ; Wu, Pei ; Liu, Weiping ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, no. 11, p. 2117-2126

Recommender systems represent an important tool for news distribution on the Internet. In this work we modify a recently proposed social recommendation model in order to deal with no explicit ratings of users on news. The model consists of a network of users which continually adapts in order to achieve an efficient news traffic. To optimize the network’s topology we propose different stochastic...

Université de Fribourg

Negative ratings play a positive role in information filtering

Zeng, Wei ; Zhu, Yu-Xiao ; Lü, Linyuan ; Zhou, Tao

In: Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, no. 23-24, p. 4486-4493

The explosive growth of information asks for advanced information filtering techniques to solve the so-called information overload problem. A promising way is the recommender system which analyzes the historical records of users’ activities and accordingly provides personalized recommendations. Most recommender systems can be represented by user-object bipartite networks where users can...

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, ( and (, 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

Personalized recommendation via integrated diffusion on user–item–tag tripartite graphs

Zhang, Zi-Ke ; Zhou, Tao ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2010, vol. 389, no. 1, p. 179-186

Personalized recommender systems are confronting great challenges of accuracy, diversification and novelty, especially when the data set is sparse and lacks accessorial information, such as user profiles, item attributes and explicit ratings. Collaborative tags contain rich information about personalized preferences and item contents, and are therefore potential to help in providing better...

Université de Fribourg

Solving the apparent diversity-accuracy dilemma of recommender systems

Zhou, Tao ; Kuscsik, Zoltán ; Liu, Jian-Guo ; Medo, Matúš ; Wakeling, Joseph Rushton ; Zhang, Yi-Cheng

In: Proceedings of the National Academy of Sciences of the USA - PNAS, 2010, vol. 107, no. 10, p. 4511-4515

Recommender systems use data on past user preferences to predict possible future likes and interests. A key challenge is that while the most useful individual recommendations are to be found among diverse niche objects, the most reliably accurate results are obtained by methods that recommend objects based on user or object similarity. In this paper we introduce a new algorithm specifically to...

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...