Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …

An algorithm for link prediction in a bipartite network is presented. In the algorithm, we first
map the bipartite network onto a unipartite network called a projected graph. Based on the …

The problem of link prediction in temporal networks has attracted considerable recent
attention from various domains, such as sociology, anthropology, information science, and …

Recently, link prediction studies on large-scale and complex networks have particularly
become the focus of interest for researchers in various scientific fields. Many complex …

With the rapid growth of the Internet in recent years, online social media has become very
important for people. People often use social media tools to communicate and share their …

Bipartite networks that characterize complex relationships among data arise in various
domains. The existing bipartite network models are mainly based on a type of relationship …

A bipartite network is an important type of complex network in human social activities.
Newman defined modularity as a measurement for evaluating community structure in …

We report higher-order coupling induced stable chimeralike state in a bipartite network of
coupled phase oscillators without any time-delay in the coupling. We show that the higher …

Bipartite graphs are a prevalent modeling tool for real-world networks, capturing interactions
between vertices of two different types. Within this framework, bicliques emerge as crucial …

The Internet has become an indispensable part of human life in today. People can now
easily find answers to questions they are curious about via the internet. The short, effortless …