K-plexes are a formal yet flexible way of defining communities in networks. They 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 up the search by several orders of magnitude, leveraging on (i) methods for strongly reducing the search space and (ii) efficient techniques for the computation of maximal cliques. Several experiments show that our strategy is effective 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.

Fast enumeration of large k-Plexes / Conte, Alessio; Firmani, Donatella; Mordente, Caterina; Patrignani, Maurizio; Torlone, Riccardo. - (2017), pp. 115-124. (Intervento presentato al convegno 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017 tenutosi a Halifax; Canada) [10.1145/3097983.3098031].

Fast enumeration of large k-Plexes

Firmani Donatella;
2017

Abstract

K-plexes are a formal yet flexible way of defining communities in networks. They 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 up the search by several orders of magnitude, leveraging on (i) methods for strongly reducing the search space and (ii) efficient techniques for the computation of maximal cliques. Several experiments show that our strategy is effective 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.
2017
23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017
Software; Information Systems
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Fast enumeration of large k-Plexes / Conte, Alessio; Firmani, Donatella; Mordente, Caterina; Patrignani, Maurizio; Torlone, Riccardo. - (2017), pp. 115-124. (Intervento presentato al convegno 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017 tenutosi a Halifax; Canada) [10.1145/3097983.3098031].
File allegati a questo prodotto
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1640572
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 41
  • ???jsp.display-item.citation.isi??? 28
social impact