Studying the topology of a network is critical to inferring underlying dynamics such as
tolerance to failure, group behavior and spreading patterns. k-core decomposition is a well …

This study considers a class of critical node detection problems that involves minimization of
a distance‐based connectivity measure of a given unweighted graph via the removal of a …

The k-plex model is a relaxation of the clique model by allowing every vertex to miss up to k
neighbors. Designing exact and efficient algorithms for computing a maximum k-plex in a …

In a graph, a k-plex is a vertex set in which every vertex is not adjacent to at most k vertices
of this set. The maximum k-plex problem, which asks for the largest k-plex from the given …

Clique is one of the most fundamental models for cohesive subgraph mining in network
analysis. Existing clique model mainly focuses on unsigned networks. In real world …

The problem of enumerating (ie, generating) all maximal cliques in a graph has received
extensive treatment, due to the plethora of applications in various areas such as data …

The concept of the clique, originally introduced as a model of a cohesive subgroup in the
context of social network analysis, is a classical model of a cluster in networks. However, the …

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 …

Given a graph, the k-plex is a vertex set in which each vertex is not adjacent to at most k− 1
other vertices in the set. The maximum k-plex problem, which asks for the largest k-plex from …

Abstract The Maximum k-Plex Search (MPS) can find the largest k-plex, which is a
generalization of the largest clique. Although MPS is commonly used in AI to effectively …