Mining maximal subgraphs with cohesive structures from a bipartite graph has been widely
studied. One important cohesive structure on bipartite graphs is k-biplex, where each vertex …

As a typical most-to-most connected quasi-biclique model, k-biplex is a superset of
bicliques, which allows nodes on each side of a fully connected subgraph to lose at most k …

As a fundamental problem in graph data mining, Densest Subgraph Discovery (DSD) aims
to find the subgraph with the highest density from a graph. It has been studied for several …

With the advent of a wide spectrum of recent applications, querying large heterogeneous
information networks (HINs) has received a great deal of attention from both academic and …

Bipartite graphs have been widely used to model the relationship between entities of
different types, where vertices are partitioned into two disjoint sets/sides. Finding dense …

Enumerating maximal k-biplexes (MBPs) of a bipartite graph has been used for applications
such as fraud detection. Nevertheless, there usually exists an exponential number of MBPs …

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 …

Finding cohesive subgraphs from a bipartite graph is a fundamental operator in bipartite
graph analysis. In this paper, we focus on the problem of mining cohesive subgraphs from a …

Bipartite graph is an important type of data structure where vertices are divided into two
disjoint sets at two sides and each edge connects a vertex at one side and another at the …

Graphs are widely used to model entities and their relationships in different domains and
some examples include social networks and biological networks. To analyse these graph …