Detecting a community in a network is a matter of discerning the distinct features and
connections of a group of members that are different from those in other communities. The …

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 …

Local graph clustering methods aim to find a cluster of nodes by exploring a small region of
the graph. These methods are attractive because they enable targeted clustering around a …

Community structure is ubiquitous in real-world complex networks. The task of community
detection over these networks is of paramount importance in a variety of applications …

Given a graph G and a vertex q∈ G, the community search query returns a subgraph of G
that contains vertices related to q. Communities, which are prevalent in attributed graphs …

Recently, the topic of community search (CS) has gained plenty of attention. Given a query
vertex, CS looks for a dense subgraph that contains it. Existing studies mainly focus on …

Recently, community search over graphs has attracted significant attention and many
algorithms have been developed for finding dense subgraphs from large graphs that contain …

Communities are prevalent in social networks, knowledge graphs, and biological networks.
Recently, the topic of community search (CS) has received plenty of attention. Given a query …

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 …

Recently, the topic of influential community search has gained much attention. Given a
graph, it aims to find communities of vertices with high importance values from it. Existing …