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 …

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 …

We consider the community search problem defined upon a large graph G: given a query
vertex q in G, to find as output all the densely connected subgraphs of G, each of which …

Community search is important in graph analysis and can be used in many real applications.
In the literature, various community models have been proposed. However, most of them …

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

We study the problem of structural graph clustering, a fundamental problem in managing
and analyzing graph data. Given an undirected unweighted graph, structural graph …

In social networks, the leave of critical users may significantly break network engagement,
ie, lead a large number of other users to drop out. A popular model to measure social …

In this paper, we study the problem of the anchored k-core. Given a graph G, an integer k
and a budget b, we aim to identify b vertices in G so that we can determine the largest …

Community search is a fundamental problem in social network mining, which has attracted
much attention in recent years. However, most previous community models only consider …

Communities serve as basic structures for understanding the organization of many real-
world networks, such as social, biological, collaboration, and communication networks …