Fast Enumeration of Large k-Plexes

Alessio Conte, Donatella Firmani, Caterina Mordente, Maurizio Patrignani, Riccardo Torlone
2017 Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '17  
k-plexes are a formal yet exible way of de ning communities in networks. ey generalize the notion of cliques and are more appropriate in most real cases: while a node of a clique C is connected to all other nodes of C, a node of a k-plex may miss up to k connections. Unfortunately, computing all maximal k-plexes is a gruesome task and state-of-the-art algorithms can only process small-size networks. In this paper we propose a new approach for enumerating large k-plexes in networks that speeds
more » ... the search by several orders of magnitude, leveraging on (i) methods for strongly reducing the search space and (ii) e cient techniques for the computation of maximal cliques. Several experiments show that our strategy is e ective and is able to increase the size of the networks for which the computation of large k-plexes is feasible from a few hundred to several hundred thousand nodes. ACM Reference format: Alessio Conte, Donatella Firmani, Caterina Mordente, Maurizio Patrignani, and Riccardo Torlone.
doi:10.1145/3097983.3098031 dblp:conf/kdd/ConteFMPT17 fatcat:q6bjujltrjc77dv4mju2nule7e