With the prevalence of Internet access and online services, various big graphs are
generated in many real applications (eg, online social networks and knowledge graphs). An …

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

Community search aims at finding densely connected subgraphs for query vertices in a
graph. While this task has been studied widely in the literature, most of the existing works …

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

Graphs are commonly used for representing complex structures such as social relationships,
biological interactions, and knowledge bases. In many scenarios, graphs not only represent …

Geo-social group search aims to find a group of people proximate to a location while socially
related. One of the driven applications for geo-social group search is organizing an …

Community search is a fundamental graph processing task that aims to find a community
containing the given query node. Recent studies show that machine learning (ML)-based …

Given a graph G and a query node q, community search (CS) aims to find a structurally
cohesive subgraph from G that contains q. CS is widely used in many real-world …

In applications such as biological, social, and transportation networks, interactions between
objects span multiple aspects. For accurately modeling such applications, multilayer …

Target community search aims to search cohesive communities consistent with the user's
preference revealed by query nodes, which is a query-dependent variant of community …