Community structure plays an important role in social networks, which can reveal potential
social relationships and deliver vast economic benefits to enterprises and organizations …

A large payment network contains millions of merchants and billions of transactions, and the
merchants are described in a large number of attributes with incomplete values …

Community Search, or finding a connected subgraph (known as a community) containing
the given query nodes in a social network, is a fundamental problem. Most of the existing …

Learning representation of networks is increasingly important in social network analysis.
Network embedding techniques have a wide range of applications in various downstream …

Most existing community-related studies focus on detection, which aim to find the community
membership for each user from user friendship links. However, membership alone, without a …

Community detection can reveal real social relations and enable great economic benefits for
enterprises and organizations; however, it can also cause privacy problems such as the …

Community is an important property of networks. Recently, label propagation based
community detection algorithms develop rapidly, since they can discover communities with …

Finding a set of co-clusters in a bipartite network is a fundamental and important problem. In
this paper, we present the Attributed Bipartite Co-clustering (ABC) problem which unifies two …

This paper proposes LinkBlackHole ^**, a novel algorithm for finding communities that are (i)
overlapping in nodes and (ii) mixing (not separating clearly) in links. There has been a small …

Force-directed algorithms are a class of methods widely used to solve problems modeled
via physics laws and resolved by particle simulation. Visualization of general graphs is one …