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 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 …

Community search is a fundamental graph mining task. Unfortunately, most previous
community search studies focus mainly on identifying communities in a network without …

The problem of k-truss search has been well defined and investigated to find the highly
correlated user groups in social networks. But there is no previous study to consider the …

Efficiently computing k-edge connected components in a large graph, G=(V, E), where V is
the vertex set and E is the edge set, is a long standing research problem. It is not only …

Given a scientific collaboration network, how can we find a group of collaborators with high
research indicator (eg, h-index) and diverse research interests? Given a social network, how …

The model of k-core and its decomposition have been applied in various areas, such as
social networks, the world wide web, and biology. A graph can be decomposed into an …

Recently, the topic of truss computation has gained plenty of attention, where the k-truss of a
graph is the maximum subgraph in which each edge participates in at least (k-2) triangles …

Community search on attributed networks has recently attracted great deal of research
interest. However, most of existing works require query users to specify some community …

Clique is one of the most fundamental models for cohesive subgraph mining in network
analysis. Existing clique model mainly focuses on unsigned networks. In real world …