Recently, the topic of influential community search has gained much attention. Given a
graph, it aims to find communities of vertices with high importance values from it. Existing …

Community search (CS) over attributed heterogeneous information networks (AHINs) takes
both network structure and attributes of nodes into consideration, which can support …

Size-constrained community search, retrieving a size-bounded high-quality subgraph
containing user-specified query vertices, has been extensively studied in graph analysis …

Community search is a personalized community discovery problem designed to identify
densely connected subgraphs containing the query node. Recently, community search in …

Attributed Heterogeneous Information Networks (AHINs) amalgamate the advantages of
attributed graphs (AGs) and heterogeneous information networks (HINs) to model intri-cate …

Community search is a personalized community discovery problem aimed at finding densely-
connected subgraphs containing the query vertex. In particular, the search for communities …

As multi-layer graphs can give a more accurate and reliable picture of the complex
relationships between entities, cohesive subgraph mining, a fundamental task in graph …

Querying cohesive subgraphs on temporal graphs (eg, social network, finance network, etc.)
with various conditions has attracted intensive research interests recently. In this paper, we …

Cohesive multipartite subgraphs (CMS) in heterogeneous information networks (HINs)
uncover closely connected vertex groups of multiple types, enhancing real applications like …

Many large-scale machine learning approaches and graph algorithms are proposed
recently to address a variety of problems in online social networks (OSNs). To evaluate and …