A novel approach to text clustering using genetic algorithm based on the nearest neighbour heuristic. Issue 3 (4th March 2022)

• Record Type: Journal Article
• Authors: Mustafi, D.; Mustafi, A.; Sahoo, G.
• Is Part Of: International journal of computers and applications. Volume 44:Issue 3(2022)
• Page Start: 291
• Page End: 303
• Publication Date: 2022-03-04
• Subjects: K-means -- genetic algorithm (GA) -- nearest neighbour separation (NNS) -- document clustering -- document representation -- cluster purity; Computers -- Periodicals; Computer software -- Periodicals; Computer networks -- Periodicals; Multimedia systems -- Periodicals; Internet -- Periodicals; World Wide Web -- Periodicals; Minicomputers -- Periodicals; Microcomputers -- Periodicals; 004.05
• DOI: 10.1080/1206212X.2020.1735035
• Languages: English
• ISSNs: 1206-212X

Abstract

Abstract : In this paper, we propose a novel clustering algorithm which uses a weighted combination of several criteria as its fitness function. We demonstrate the suitability of the new method in the case of clustering text documents. The proposed algorithm leverages the concept of nearest neighbour separation (NNS) to enhance the separation of the clusters and also outlines a heuristic to compute the NNS. A new parameterized fitness function has been proposed which can be tuned to provide more weightage to the traditional metrics based on inter- and intra-cluster distances of clusters or on the NNS. Genetic Algorithm has been used to perform the actual clustering and the results obtained has been compared with the traditional K-Means algorithm. The performance of the algorithm has been tested on different standard datasets, and the results have been presented.