Faster maximal clique enumeration in large real-world link streams

TL;DR

This paper introduces a faster algorithm for enumerating maximal cliques in large link streams, significantly outperforming existing methods and scaling to massive datasets with up to 100 million links.

Contribution

A novel algorithm based on the Bron-Kerbosch approach that improves efficiency and scalability for maximal clique enumeration in large, real-world link streams.

Findings

Algorithm is at least 10 times faster than previous methods.

Scales to link streams with up to 100 million links.

Outperforms state-of-the-art algorithms in various large datasets.

Abstract

Link streams offer a good model for representing interactions over time. They consist of links $(b,e,u,v)$, where $u$ and $v$ are vertices interacting during the whole time interval $[b,e]$. In this paper, we deal with the problem of enumerating maximal cliques in link streams. A clique is a pair $(C,[t_0,t_1])$, where $C$ is a set of vertices that all interact pairwise during the full interval $[t_0,t_1]$. It is maximal when neither its set of vertices nor its time interval can be increased. Some of the main works solving this problem are based on the famous Bron-Kerbosch algorithm for enumerating maximal cliques in graphs. We take this idea as a starting point to propose a new algorithm which matches the cliques of the instantaneous graphs formed by links existing at a given time $t$ to the maximal cliques of the link stream. We prove its validity and compute its complexity, which is better than the state-of-the art ones in many cases of interest. We also study the output-sensitive complexity, which is close to the output size, thereby showing that our algorithm is efficient. To confirm this, we perform experiments on link streams used in the state of the art, and on massive link streams, up to 100 million links. In all cases our algorithm is faster, mostly by a factor of at least 10 and up to a factor of $10^4$. Moreover, it scales to massive link streams for which the existing algorithms are not able to provide the solution.