Community search over large dynamic graph has become an important research problem in
modern complex networks, such as the online social network, collaboration network and …

Searching for local communities is an important research challenge that allows for
personalized community discovery and supports advanced data analysis in various complex …

Higher-order graph clustering aims to partition the graph using frequently occurring
subgraphs (ie, motifs), instead of the lower-order edges, as the atomic clustering unit, which …

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

Searching for local communities is an important research problem that supports advanced
data analysis in various complex networks, such as social networks, collaboration networks …

Maximal clique enumeration is a fundamental operator in graph analysis. The model of
clique, however, is typically too restrictive for real-world applications as it requires an edge …

Temporal community search is an important task in graph analysis, which has been widely
used in many practical applications. However, existing methods suffer from two major …

Mining cohesive subgraphs from a graph is a fundamental problem in graph data analysis.
One notable cohesive structure is γ-quasi-clique (QC), where each vertex connects at least a …

Real-world networks, such as social networks, cryptocurrency networks, and e-commerce
networks, always have occurrence time of interactions between nodes. Such networks are …

Finding dense subnetworks, with density based on edges or more complex structures, such
as subgraphs or k-cliques, is a fundamental algorithmic problem with many applications …