In: The European Physical Journal B, 2008, vol. 66, no. 4, p. 557-561
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In: The European Physical Journal B, 2009, vol. 71, no. 4, p. 623-630
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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...
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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...
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In: The Scientific World Journal, 2013, vol. 2013, p. -
An SEI autonomous model with logistic growth rate and its corresponding nonautonomous model are investigated. For the autonomous case, we give the attractive regions of equilibria and perform some numerical simulations. Basic demographic reproduction Rd number is obtained. Moreover, only the basic reproduction number R0 cannot ensure the existence of the positive equilibrium, which needs...
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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...
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In: PLoS ONE, 2013, vol. 8, no. 2, p. e55437
Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and...
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In: Physica A: Statistical Mechanics and its Applications, 2012, vol. 139, no. 22, p. 5769–5778
To evaluate the performance of prediction of missing links, the known data are randomly divided into two parts, the training set and the probe set. We argue that this straightforward and standard method may lead to terrible bias, since in real biological and information networks, missing links are more likely to be links connecting low-degree nodes. We therefore study how to uncover missing links...
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In: Physics Reports, 2012, vol. 519, no. 1, p. 1–49
The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification...
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In: Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 2012, vol. 85, no. 4, p. 046108
The advent of the Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. It has thus become important to address issues like who gets followed and how to allow people to discover new and better information sources. In this paper we conduct an...
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