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 …

We study the discovery of cliques (or" complete" subgraphs) in heterogeneous information
networks (HINs). Existing clique-finding solutions often ignore the rich semantics of HINs …

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 …

Due to the sheer size of real-world networks, delay and space become quite relevant
measures for the cost of enumeration in network analytics. This paper presents efficient …

We propose a new distribution-free model of social networks. Our definitions are motivated
by one of the most universal signatures of social networks, triadic closure---the property that …

The maximum k-plex, a generalization of maximum clique, is used to cope with a great
number of real-world problems. The aim of this paper is to propose a novel exact k-plex …

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 …

We propose a novel graph pooling operation using cliques as the unit pool. As this
approach is purely topological, rather than featural, it is more readily interpretable, a better …

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 …

Due to the sheer size of real-world networks, delay and space have become quite relevant
measures of the cost of enumerating patterns for network analytics. This paper presents …