There is an increasing number of researches of complex networks such as the WWW, social networks and biological networks. One of the hot topics in this area is community detection. Nodes belonging to a community are likely to have common properties. For instance, in the WWW, a community may be a set of pages which belong to a same topic. Community structure is undoubtedly a key characteristic of complex networks. In this paper, we propose a new framework for finding communities in complex networks.This framework uses the idea of intersection graph and uses semantic information such as texts and attributes which appear in networks. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Okada, N., Tanikawa, K., Hijikata, Y., & Nishida, S. (2010). A framework for finding community in complex networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6193 LNCS, pp. 308–315). https://doi.org/10.1007/978-3-642-14589-6_31
Mendeley helps you to discover research relevant for your work.