This paper studies k-plexes, a well known pseudo-clique model for network communities. In
a k-plex, each node can miss at most k-1 links. Our goal is to detect large communities in …

Listing dense subgraphs in large graphs plays a key task in varieties of network analysis
applications like community detection. Clique, as the densest model, has been widely …

The problem of enumerating all maximal cliques in a graph is a key primitive in a variety of
real-world applications such as community detection and so on. However, in practice …

Finding all maximal k-plexes on networks is a fundamental research problem in graph
analysis due to many important applications, such as community detection, biological graph …

K-plexes are a formal yet flexible way of defining communities in networks. They generalize
the notion of cliques and are more appropriate in most real cases: while a node of a clique C …

Maximal clique enumeration on uncertain graphs is a fundamental problem in uncertain
graph analysis. In this paper, we study a problem of enumerating all maximal (k, n)-cliques …

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 …

An enumeration problem is the task of listing a set of elements without redundancies, usually
the solutions of some combinatorial problem. The enumeration of cycles in a graph …

Maximal k-plex enumeration is an important problem in graph analysis and can find many
real-world applications. A k-plex is a subgraph in which every vertex can miss edges to at …

Maximal Clique Enumeration (MCE) is a fundamental graph mining problem and is useful as
a primitive in identifying dense structures in a graph. Due to the high computational cost of …