Journal of the Visualization Society of Japan
Online ISSN : 1884-037X
Print ISSN : 0916-4731
ISSN-L : 0916-4731
Reviews
Visualization of Functional Community Structure in Complex Network
Takayasu FUSHIMIKazumi SAITOKazuhiro KAZAMA
Author information
JOURNAL FREE ACCESS
Supplementary material

2016 Volume 36 Issue 141 Pages 14-20

Details
Abstract

In this paper, in order to reveal the characteristics and functions of many networks with complex structure, we explain a framework that extracts communities with different point of view and colors all the nodes of visualization results according to the extracted communities. In real networks, each node has intrinsic functions and roles, and mutually affects on other nodes. In this paper, different from existing community of densely connected nodes, we extract the nodes with similar functions, referred to as functional community. Concretely, we calculate the PageRank score convergence curve of each node and divide all nodes by similarities of these curves as functional community. Finally we color all the node with respect to functional community. From experimental results using artificial and real networks, we confirm that our framework can extract adequate functional communities.

Content from these authors
© 2016 The Visualization Society of Japan
Previous article Next article
feedback
Top