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Université de Fribourg

The long-term impact of ranking algorithms in growing networks

Zhang, Shilun ; Medo, Matúš ; Lü, Linyuan ; Mariani, Manuel Sebastian

In: Information Sciences, 2019, vol. 488, p. 257–271

When users search online for content, they are constantly exposed to rankings. For example, web search results are presented as a ranking of relevant websites, and online bookstores often show us lists of best-selling books. While popularity-based ranking algorithms (like Google’s PageRank) have been extensively studied in previous works, we still lack a clear understanding of their...

Université de Fribourg

Link prediction in bipartite nested networks

Medo, Matúš ; Mariani, Manuel Sebastian ; Lü, Linyuan

In: Entropy, 2018, vol. 20, no. 10, p. 777

Real networks typically studied in various research fields—ecology and economic complexity, for example—often exhibit a nested topology, which means that the neighborhoods of high-degree nodes tend to include the neighborhoods of low-degree nodes. Focusing on nested networks, we study the problem of link prediction in complex networks, which aims at identifying likely candidates for...

Consortium of Swiss Academic Libraries

The role of a matchmaker in buyer-vendor interactions

Lü, Linyuan ; Medo, M. ; Zhang, Y.-C

In: The European Physical Journal B, 2009, vol. 71, no. 4, p. 565-571

Consortium of Swiss Academic Libraries

Empirical analysis on a keyword-based semantic system

Zhang, Zi-Ke ; Lü, Linyuan ; Liu, Jian-Guo ; Zhou, Tao

In: The European Physical Journal B, 2008, vol. 66, no. 4, p. 557-561

Consortium of Swiss Academic Libraries

Predicting missing links via local information

Zhou, Tao ; Lü, Linyuan ; Zhang, Yi-Cheng

In: The European Physical Journal B, 2009, vol. 71, no. 4, p. 623-630

Université de Fribourg

Toward link predictability of complex networks

Lü, Linyuan ; Pan, Liming ; Zhou, Tao ; Zhang, Yi-Cheng ; Stanley, H. Eugene

In: Proceedings of the National Academy of Sciences, 2015, vol. 112, no. 8, p. 2325–2330

The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in...

Université de Fribourg

Avoiding congestion in recommender systems

Ren, Xiaolong ; Lü, Linyuan ; Liu, Runran ; Zhang, Jianlin

In: New Journal of Physics, 2014, vol. 16, no. 6, p. 063057

Recommender systems use the historical activities and personal profiles of users to uncover their preferences and recommend objects. Most of the previous methods are based on objects' (and/or users') similarity rather than on their difference. Such approaches are subject to a high risk of increasingly exposing users to a narrowing band of popular objects. As a result, a few objects may be...

Université de Fribourg

Identifying influential spreaders by weighted LeaderRank

Li, Qian ; Zhou, Tao ; Lü, Linyuan ; Chen, Duanbing

In: Physica A: Statistical Mechanics and its Applications, 2014, vol. 404, p. 47–55

Identifying influential spreaders is crucial for understanding and controlling spreading processes on social networks. Via assigning degree-dependent weights onto links associated with the ground node, we proposed a variant to a recent ranking algorithm named LeaderRank (Lü et al., 2011). According to the simulations on the standard SIR model, the weighted LeaderRank performs better than...

Université de Fribourg

Identifying influential nodes in large-scale directed networks: the role of clustering

Chen, Duan Bing ; Gao, Hui ; Lü, Linyuan ; Zhou, Tao

In: PLoS ONE, 2013, vol. 8, no. 10, p. e77455

Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to...

Université de Fribourg

The power of ground user in recommender systems

Zhou, Yanbo ; Lü, Linyuan ; Liu, Weiping ; Zhang, Jianlin

In: PLoS ONE, 2013, vol. 8, no. 8, p. e70094

Accuracy and diversity are two important aspects to evaluate the performance of recommender systems. Two diffusion-based methods were proposed respectively inspired by the mass diffusion (MD) and heat conduction (HC) processes on networks. It has been pointed out that MD has high recommendation accuracy yet low diversity, while HC succeeds in seeking out novel or niche items but with relatively...