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Clustering of Words in Texts Using Fuzzy Neighborhood

Authors:
CanLun Zhang
Sadaaki Miyamoto

Keywords: kernel-based clustering; fuzzy neighborhood; c-means; keywords in texts

Abstract:
In this paper, we study the clustering of keywords in documents. We consider a model of fuzzy neighborhood for measuring similarity between words. Fuzzy neighborhoods lead to positive-definite kernels. By using the methods of kernel-based fuzzy c-means and affinity propagation, we show the results of clustering for Chinese documents on the Web. Moreover, Rand index is used to compare robustness of hard and fuzzy c-means algorithms with respect to different initial values.

Pages: 5 to 8

Copyright: Copyright (c) IARIA, 2015

Publication date: May 24, 2015

Published in: conference

ISSN: 2308-4332

ISBN: 978-1-61208-408-4

Location: Rome, Italy

Dates: from May 24, 2015 to May 29, 2015