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 …

The diffusion method is one of the main methods of community detection in complex
networks. In this method, the use of the concept that diffusion within the nodes that are …

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 …

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 …

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 …

Bipartite graphs are widely used to model relation-ships between two types of entities.
Community search retrieves densely connected subgraphs containing a query vertex, which …

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 …

Derived from the idea of word-to-mouth advertising and with applying information diffusion
theory, viral marketing attracts wide research interests because of its business value. As an …