With the rapid development of information technologies, various big graphs are prevalent in
many real applications (eg, social media and knowledge bases). An important component of …

Community detection which discovers densely connected structures in a network has been
studied a lot. In this paper, we study online community search which is practically useful but …

The k-truss is a type of cohesive subgraphs proposed recently for the study of networks.
While the problem of computing most cohesive subgraphs is NP-hard, there exists a …

Community search is important in social network analysis. For a given vertex in a graph, the
goal is to find the best community the vertex belongs to. Intuitively, the best community for a …

Community search is a problem of finding densely connected subgraphs that satisfy the
query conditions in a network, which has attracted much attention in recent years. However …

Studying the topology of a network is critical to inferring underlying dynamics such as
tolerance to failure, group behavior and spreading patterns. k-core decomposition is a well …

Recently, there has been significant interest in the study of the community search problem in
social and information networks: given one or more query nodes, find densely connected …

The core decomposition of networks has attracted significant attention due to its numerous
applications in real-life problems. Simply stated, the core decomposition of a network …

Among the novel metrics used to study the relative importance of nodes in complex
networks, k-core decomposition has found a number of applications in areas as diverse as …

Densest subgraph discovery (DSD) is a fundamental problem in graph mining. It has been
studied for decades, and is widely used in various areas, including network science …