CLAM: Clustering Large Applications using Metaheuristics

Nguyen, Quynh and Rayward-Smith, V. J. (2011) CLAM: Clustering Large Applications using Metaheuristics. Journal of Mathematical Modelling and Algorithms, 10 (1). pp. 57-78. ISSN 1570-1166

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Abstract

Clustering remains one of the most difficult challenges in data mining. This paper proposes a new algorithm, CLAM, using a hybrid metaheuristic between VNS and Tabu Search to solve the problem of k-medoid clustering. The new technique is compared to the well-known CLARANS. Experimental results show that, given the same computation times, CLAM is more effective.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: Vishal Gautam
Date Deposited: 04 Mar 2011 15:09
Last Modified: 21 Apr 2020 16:38
URI: https://ueaeprints.uea.ac.uk/id/eprint/21854
DOI: 10.1007/s10852-010-9141-1

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