By Topic

AHSCAN: Agglomerative Hierarchical Structural Clustering Algorithm for Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Yuruk, N. ; Appl. Sci., Univ. of Arkansas at Little Rock, Little Rock, AR, USA ; Mete, M. ; Xiaowei Xu ; Schweiger, T.A.J.

Many systems in sciences, engineering and nature can be modeled as networks. Examples include the Internet, WWW and social networks. Finding hidden structures is important for making sense of complex networked data. In this paper we present a new network clustering method that can find clusters in an agglomerative fashion using structural similarity of vertices in the given network. Experiments conducted on real datasets demonstrate promising performance of the new method.

Published in:

Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in

Date of Conference:

20-22 July 2009