Journal of Advances in Technology and Engineering Research
Journal ISSN: 2414-4592
Artical DOI:
Received: 19 October 2014
Accepted: 20 July 2015
Published: 26 April 2016
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  • Document overlapping clustering using formal concept analysis

Yi-Hui Chen , Eric Jui-Lin Lu ,Yu-Ting Lin , Ya-Wen Cheng

Published online: 2016


Text document clustering is a technique which groups documents into several clusters based on the similarities among documents. Most clustering algorithms build disjoint clusters, but clusters should be overlapped because documents may belong to two or more categories in real world. For example, an article discussing the Apple Watch may be categorized into either 3C, Fashion, or even Clothing and Shoes. In this paper, we propose an overlapping clustering algorithm by using the Formal Concept Analysis, which could make a document assigned to two or more clusters. Moreover, our algorithm reduced the dimensions of the vector space, and performed more efficiently than existing clustering methods.