Enumerating maximal cliques in link streams with durations

TL;DR

This paper extends the concept of maximal cliques in link streams to include interactions with durations, providing a generalized framework and an improved algorithm that outperforms existing methods in various scenarios.

Contribution

It generalizes the notion of cliques in link streams to include durations and introduces an improved algorithm for detecting maximal cliques.

Findings

The new algorithm outperforms previous methods in multiple cases.

The instantaneous interaction case is a special instance of the generalized model.

The approach enhances detection of maximal cliques in temporal interaction data.

Abstract

Link streams model interactions over time, and a clique in a link stream is defined as a set of nodes and a time interval such that all pairs of nodes in this set interact permanently during this time interval. This notion was introduced recently in the case where interactions are instantaneous. We generalize it to the case of interactions with durations and show that the instantaneous case actually is a particular case of the case with durations. We propose an algorithm to detect maximal cliques that improves our previous one for instantaneous link streams, and performs better than the state of the art algorithms in several cases of interest.