Com2: Fast automatic discovery of temporal ('comet') communities
Com2: Fast automatic discovery of temporal ('comet') communities
dc.contributor.author | Miguel Ramos Araújo | en |
dc.contributor.author | Papadimitriou,S | en |
dc.contributor.author | Gunnemann,S | en |
dc.contributor.author | Faloutsos,C | en |
dc.contributor.author | Basu,P | en |
dc.contributor.author | Swami,A | en |
dc.contributor.author | Papalexakis,EE | en |
dc.contributor.author | Koutra,D | en |
dc.date.accessioned | 2018-01-19T11:06:21Z | |
dc.date.available | 2018-01-19T11:06:21Z | |
dc.date.issued | 2014 | en |
dc.description.abstract | Given a large network, changing over time, how can we find patterns and anomalies? We propose Com2, a novel and fast, incremental tensor analysis approach, which can discover both transient and periodic/ repeating communities. The method is (a) scalable, being linear on the input size (b) general, (c) needs no user-defined parameters and (d) effective, returning results that agree with intuition. We apply our method on real datasets, including a phone-call network and a computer-traffic network. The phone call network consists of 4 million mobile users, with 51 million edges (phonecalls), over 14 days. Com2 spots intuitive patterns, that is, temporal communities (comet communities). We report our findings, which include large 'star'-like patterns, nearbipartite- cores, as well as tiny groups (5 users), calling each other hundreds of times within a few days. © 2014 Springer International Publishing. | en |
dc.identifier.uri | http://repositorio.inesctec.pt/handle/123456789/7062 | |
dc.identifier.uri | http://dx.doi.org/10.1007/978-3-319-06605-9_23 | en |
dc.language | eng | en |
dc.relation | 6311 | en |
dc.rights | info:eu-repo/semantics/openAccess | en |
dc.title | Com2: Fast automatic discovery of temporal ('comet') communities | en |
dc.type | conferenceObject | en |
dc.type | Publication | en |
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