TEXT DOCUMENT CLUSTERING USING ARTIFICIAL BEE COLONY WITH BISECTING K-MEANS ALGORITHM

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Published: Feb 20, 2018
DOI: https://doi.org/10.26483/ijarcs.v9i1.5359
Keywords:
Document Clustering, ABC Algorithm, K-means, Bisecting K-means, ABC-BK

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Janani Balakumar
Bharathiar University Coimbatore - 46
Dr. S. Vijayarani

Abstract

Recently, document clustering with optimization techniques has gained the attention of many researchers, especially those who are dealing with a huge volume of documents. The main goal of document clustering is to place the documents with similar content in one group, and the documents with dissimilar contents in another group. Document clustering with optimization algorithm achieves the global optimal solution. The main aim of this research work is to cluster the documents based on their content. In order to perform this task, this research work proposes a new hybrid algorithm called Artificial Bee Colony with Bisecting K-Means (ABC-BK). The proposed algorithm was verified with the benchmark dataset in contrast to the widely used document clustering algorithms. Experimental results show that the proposed algorithm gives a better performance compared to the standard ABC clustering algorithm, K-means, and the Bisecting K-means algorithm.

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Vol. 9 No. 1 (2018): January-February 2018
Section
Articles

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