Real networks exhibit heterogeneous nature with nodes playing far different roles in
structure and function. To identify vital nodes is thus very significant, allowing us to control …

The ongoing rapid expansion of the Internet greatly increases the necessity of effective
recommender systems for filtering the abundant information. Extensive research for …

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 …

Identifying influential nodes in dynamical processes is crucial in understanding network
structure and function. Degree, H-index and coreness are widely used metrics, but …

Google's PageRank method was developed to evaluate the importance of web-pages via
their link structure. The mathematics of PageRank, however, are entirely general and apply …

Finding an optimal set of nodes, called key players, whose activation (or removal) would
maximally enhance (or degrade) a certain network functionality, is a fundamental class of …

The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the
information of effective transmission from heterogeneous individuals to various systems …

Community detection is one of the most popular researches in a variety of complex systems,
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …

The propagations of diseases, behaviors and information in real systems are rarely
independent of each other, but they are coevolving with strong interactions. To uncover the …

Biological entities are involved in intricate and complex interactions, in which uncovering the
biological information from the network concepts are of great significance. Benefiting from …