Dense subgraph mining with a mixed graph model

Keszler, Anita and Szirányi, Tamás and Tuza, Zsolt (2013) Dense subgraph mining with a mixed graph model. PATTERN RECOGNITION LETTERS, 34 (11). pp. 1252-1262. ISSN 0167-8655 10.1016/j.patrec.2013.03.035

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In this paper we introduce a graph clustering method based on dense bipartite subgraph mining. The method applies a mixed graph model (both standard and bipartite) in a three-phase algorithm. First a seed mining method is applied to find seeds of clusters, the second phase consists of refining the seeds, and in the third phase vertices outside the seeds are clustered. The method is able to detect overlapping clusters, can handle outliers and applicable without restrictions on the degrees of vertices or the size of the clusters. The running time of the method is polynomial. A theoretical result is introduced on density bounds of bipartite subgraphs with size and local density conditions. Test results on artificial datasets and social interaction graphs are also presented.

Item Type: ISI Article
Uncontrolled Keywords: Graph theory, Mining, Three-phase algorithms, Overlapping clusters, Mixed graph, Dense subgraph, Bipartite subgraphs, Artificial datasets, Social graphs, Mixed graph model, Graph clustering, Dense subgraph mining, Cluster seed mining
Subjects: Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions: Distributed Events Analysis Research Laboratory
SWORD Depositor: MTMT Injector
Depositing User: EPrints Admin
Date Deposited: 05 Feb 2014 12:32
Last Modified: 15 May 2014 11:04

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