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Exploring a Community Clustering Algorithm on Semantic Similarity in Large-Scale Social Network

Authors:
Laizhong Cui
Yuanyuan Jin
Nan Lu

Keywords: semantic similarity; WordNet ontology; social network; community structure; clustering algorithm; key concept set

Abstract:
This paper proposes a semantic similarity clustering algorithm on the cluster analysis of large-scale social network. By utilizing the semantic hierarchy of WordNet, the proposed method defines the key concept sets and the concept feature values for the community. In our method, the semantic relations between concepts of the community nodes are also constructed, which expands the application of clustering algorithms from text documents to social network. The cluster structures derived from the proposed algorithm are in concordance with peoples' judgments on a specific area, which will lead to the solution of the clustering problems in the social network of different areas. Compared with VSM and k-MEANS, the experiment results show that the proposed algorithm obtains more reasonable results, which validates its effectiveness.

Pages: 57 to 64

Copyright: Copyright (c) IARIA, 2015

Publication date: July 19, 2015

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-419-0

Location: Nice,France

Dates: from July 19, 2015 to July 24, 2015