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

Full text not available from this repository. (Request a copy)


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
Depositing User: Vishal Gautam
Date Deposited: 04 Mar 2011 15:09
Last Modified: 17 Jan 2024 01:20
DOI: 10.1007/s10852-010-9141-1

Actions (login required)

View Item View Item