Two-Phase Genetic Algorithm for Social Network Graphs Clustering

0427034 - ÚI 2015 RIV US eng C - Conference Paper (international conference)
Kohout, J. - Neruda, Roman
Two-Phase Genetic Algorithm for Social Network Graphs Clustering.
IEEE 27th International Conference on Advanced Information Networking and Applications Workshops. Los Alamitos: IEEE Computer Society, 2013 - (Barolli, L.; Xhafa, F.; Takizawa, M.; Enokido, T.; Hsu, H.), s. 197-202. ISBN 978-0-7695-4952-1.
[WAINA 2013. International Conference on Advanced Information Networking and Applications Workshops /27./. Barcelona (ES), 25.03.2013-28.03.2013]
R&D Projects: GA ČR GAP202/11/1368
Grant - others:European Office of Aerospace Research and Development(XE) FA8655-11-3035
Institutional support: RVO:67985807
Keywords : clustering * genetic algorithms * graph
Subject RIV: IN - Informatics, Computer Science

An important and useful task of a social network analysis is partitioning of its users into clusters. The structure of a social network can be naturally modeled by a directed graph. This approach transforms clustering of the users into searching for highly connected subgraphs in such a social network model. Many different approaches and algorithms for this problem exist, one of the possibilities is to utilize genetic algorithms for solving this type of task. In this paper, we analyze several different genetic operators and propose evolutionary based algorithm for clustering in the domain of directed weighted graphs.
Permanent Link: http://hdl.handle.net/11104/0232647