Dynamic communities and their detection

Bóta András and Krész Miklós and Pluhár András: Dynamic communities and their detection. In: Acta cybernetica, (20) 1. pp. 35-52. (2011)

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Abstract

Overlapping community detection has already become an interesting problem in data mining and also a useful technique in applications. This underlines the importance of following the lifetime of communities in real graphs. Palla et al. developed a promising method, and analyzed community evolution on two large databases [23]. We have followed their footsteps in analyzing large real-world databases and found, that the framework they use to describe the dynamics of communities is insufficient for our data. The method used by Palla et al. is also dependent on a very special community detection algorithm, the clique percolation method, and on its monotonic nature. In this paper we propose an extension of the basic community events described in [23] and a method capable of handling communities found a non-monotonic community detection algorithm. We also report on findings that came from the tests on real social graphs.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2011
Volume: 20
Number: 1
ISSN: 0324-721X
Page Range: pp. 35-52
Language: English
Place of Publication: Szeged
Event Title: Conference for PhD Students in Computer Science (7.) (2010) (Szeged)
Related URLs: http://acta.bibl.u-szeged.hu/38531/
DOI: 10.14232/actacyb.20.1.2011.4
Uncontrolled Keywords: Számítástechnika, Kibernetika
Additional Information: Bibliogr.: p. 50-52. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
Date Deposited: 2016. Oct. 15. 12:24
Last Modified: 2022. Jun. 17. 13:29
URI: http://acta.bibl.u-szeged.hu/id/eprint/12897

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