This paper addresses the theoretical analysis of synchronization between two complex networks with nonidentical topological structures. By designing effective adaptive controllers, we achieve synchronization between two complex networks. Both the cases of identical and nonidentical network...

A financial market is an example of an adaptive complex network consisting of many interacting units. This network reflects market’s behavior. In this paper, we use Random Matrix Theory (RMT) notion for specifying the largest eigenvector of correlation matrix as the market mode of stock...

Link prediction is a technique that uses the topological information in a given network to infer the missing links in it. Since past research on link prediction has primarily focused on enhancing performance for given empirical systems, negligible attention has been devoted to link prediction...

The investigation of link prediction in networks is an important issue in many disciplines. The research of prediction algorithms which required short time but high accuracy is still a challenging task. Most of the existing algorithms are based on the topological information of the networks,...

Homophily is a significant mechanism for link prediction in complex network, of which principle describes that people with similar profiles or experiences tend to tie with each other. In a multi-relationship network, friendship among people has been utilized to reinforce similarity of taste for...

Link prediction in directed network is attracting growing interest among many network scientists. Compared with predicting the existence of a link, determining its direction is more complicated. In this paper, we propose an efficient solution named Local Directed Path to predict link direction....

The probability of two nodes to be linked is related to their similarities in the network. Based on statistical inference, a network-structure similarity index, therefore, is proposed to find the potential links. This index quantifies the effects of the node communities on these links. And an...

In recent years, bipartite-networks-based recommendations have attracted the attention of many researchers. Many of them are committed to improving the recommendation algorithms such as network-based inference (NBI) or probability spreading (ProbS). However, usually one or two parameters are...

Recently, in complex network, link prediction has brought a surge of researches, among which similarity based link prediction outstandingly gains considerable success, especially similarity in terms of paths. In investigation of paths based similarity, we find that the effective influence of...

Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent...