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 …

Detecting and analyzing dense groups or communities from social and information networks
has attracted immense attention over the last decade due to its enormous applicability in …

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 …

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 …

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 …

Community detection is an important task with many applications. However, there is no
universal definition of communities, and a variety of algorithms have been proposed based …

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 …

Community search enables personalized community discovery and has wide applications in
large real-world graphs. While community search has been extensively studied for …