Clustering documents with labeled and unlabeled documents using fuzzy semi-Kmeans

While focusing on document clustering, this work presents a fuzzy semi-supervised clustering algorithm called fuzzy semi-Kmeans. The fuzzy semi-Kmeans is an extension of K-means clustering model, and it is inspired by an EM algorithm and a Gaussian mixture model. Additionally, the fuzzy semi-Kmeans...

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Bibliographic Details
Published in:	Fuzzy sets and systems Vol. 221; pp. 48 - 64
Main Authors:	Liu, Chien-Liang, Chang, Tao-Hsing, Li, Hsuan-Hsun
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 16.06.2013
Subjects:	Algorithms Clustering Focusing Fuzzy Fuzzy clustering Fuzzy logic Fuzzy semi-Kmeans Fuzzy set theory Gaussian Mathematical models Semi-supervised learning Text mining Text mining Fuzzy clustering Semi-supervised learning Fuzzy semi-Kmeans
ISSN:	0165-0114, 1872-6801
Online Access:	Get full text
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