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Complex networks have been receiving increasing attention by the scientific community, also due to the availability of massive network data from diverse domains. One problem largely studied so far is Link Prediction, i.e. the problem of predicting new upcoming connections in the network. However, one aspect of complex networks has been disregarded so far: real networks are often multidimensional,...
Network association is a prevalent representation when dealing with data from present-day applications. Examples are crime event connections in criminology, cellphone call graphs in telecommunication, co-authorship networks in bibliometrics, etc. A large body of work has been devoted to the analysis of these networks and the discovery of their underlying structures. One important structure is the...
Many algorithms have been developed to identify important nodes in a complex network, including various centrality metrics and Page Rank, but most fail to consider the dynamic nature of the network. They therefore suffer from recency bias and fail to recognize important new nodes that have not had as much time to accumulate links as their older counterparts. This paper describes the Effective Contagion...
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