Dynamic communities and their detection

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...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Bóta András
Krész Miklós
Pluhár András
Testületi szerző: Conference for PhD Students in Computer Science (7.) (2010) (Szeged)
Dokumentumtípus: Cikk
Megjelent: 2011
Sorozat:Acta cybernetica 20 No. 1
Kulcsszavak:Számítástechnika, Kibernetika
Tárgyszavak:
doi:10.14232/actacyb.20.1.2011.4

Online Access:http://acta.bibl.u-szeged.hu/12897
Leíró adatok
Tartalmi kivonat: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.
Terjedelem/Fizikai jellemzők:35-52
ISSN:0324-721X