In many real-world applications, bipartite graphs are naturally used to model relationships
between two types of entities. Community discovery over bipartite graphs is a fundamental …

Local community detection refers to finding the community that contains the given node
based on local information, which becomes very meaningful when global information about …

Community search in heterogeneous information networks (HINs) has attracted much
attention in graph analysis. Given a vertex, the goal is to find a densely-connected sub …

Community search aims at finding densely connected subgraphs for query vertices in a
graph. While this task has been studied widely in the literature, most of the existing works …

With the proliferation of graph applications, the problem of efficiently computing all k-edge
connected components of a graph G for a user-given k has been recently investigated. In …

Searching for a community based on query nodes in a graph is a fundamental problem and
has been extensively investigated. Most of the existing approaches focus on finding a …

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 …

Community detection methods aim to find nodes connected to each other more than other
nodes in a graph. As they explore the entire network, global methods suffer from severe …

As one of the most representative cohesive subgraph models, k-core model has recently
received significant attention in the literature. In this paper, we investigate the problem of the …

Community search that finds only the communities pertaining to the query input has been
widely studied from simple graphs to attributed graphs. However, a significant limitation of …