Finding all maximal connected S-cliques in social networks

Rachel Behar, Sara Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations


Cliques are commonly used for social network analysis tasks, as they are a good representation of close-knit groups of people. For this reason (as well as for others), the problem of enumerating, i.e., finding, all maximal cliques in a graph has received extensive treatment. However, considering only complete subgraphs is too restrictive in many real-life scenarios where “almost cliques” may be even more useful. Hence, the notion of an s-clique, a clique relaxation that allows every node to be at distance at most s from every other node, has been introduced. Connected s-cliques add the natural requirement of connectivity to the notion of an s-clique. This paper presents efficient algorithms for finding all maximal connected s-cliques in a graph. We present a provably efficient algorithm, which runs in polynomial delay. In addition, we present several variants of the well-known Bron-Kerbosch algorithm for maximal clique generation. Extensive experimentation over both real and synthetic datasets shows the efficiency of our algorithms, and their scalability with respect to graph size, density, and choice of s.

Original languageAmerican English
Title of host publicationAdvances in Database Technology - EDBT 2018
Subtitle of host publication21st International Conference on Extending Database Technology, Proceedings
EditorsMichael Bohlen, Reinhard Pichler, Norman May, Erhard Rahm, Shan-Hung Wu, Katja Hose
Number of pages12
ISBN (Electronic)9783893180783
StatePublished - 2018
Event21st International Conference on Extending Database Technology, EDBT 2018 - Vienna, Austria
Duration: 26 Mar 201829 Mar 2018

Publication series

NameAdvances in Database Technology - EDBT
ISSN (Electronic)2367-2005


Conference21st International Conference on Extending Database Technology, EDBT 2018

Bibliographical note

Publisher Copyright:
© 2018 Copyright held by the owner/author(s)


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