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 language||American English|
|Title of host publication||Advances in Database Technology - EDBT 2018|
|Subtitle of host publication||21st International Conference on Extending Database Technology, Proceedings|
|Editors||Michael Bohlen, Reinhard Pichler, Norman May, Erhard Rahm, Shan-Hung Wu, Katja Hose|
|Number of pages||12|
|State||Published - 2018|
|Event||21st International Conference on Extending Database Technology, EDBT 2018 - Vienna, Austria|
Duration: 26 Mar 2018 → 29 Mar 2018
|Name||Advances in Database Technology - EDBT|
|Conference||21st International Conference on Extending Database Technology, EDBT 2018|
|Period||26/03/18 → 29/03/18|
Bibliographical noteFunding Information:
The authors were partially supported by the Israel Science Foundation (Grant 879/16).
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