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 …

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 …

Aiming to alleviate data sparsity and cold-start problems of tradi-tional recommender
systems, incorporating knowledge graphs (KGs) to supplement auxiliary information has …

To alleviate data sparsity and cold-start problems of traditional recommender systems (RSs),
incorporating knowledge graphs (KGs) to supplement auxiliary information has attracted …

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 …

The problem of computing (α, β α, β)-core in a bipartite graph for given α α and β β is a
fundamental problem in bipartite graph analysis and can be used in many applications such …

The classic problem of node importance estimation has been conventionally studied with
homogeneous network topology analysis. To deal with practical network heterogeneity, a …

Attributed community search aims to find the community with strong structure and attribute
cohesiveness from attributed graphs. However, existing works suffer from two major …

Given a directed graph G, the directed densest subgraph (DDS) problem refers to the finding
of a subgraph from G, whose density is the highest among all the subgraphs of G. The DDS …