Brunel University Research Archive (BURA) >
Schools >
School of Information Systems, Computing and Mathematics >
School of Information Systems, Computing and Mathematics Research Papers >

Please use this identifier to cite or link to this item:

Title: Metaheuristic approaches for the quartet method of hierarchical clustering
Authors: Consoli, S
Darby-Dowman, K
Geleijnse, G
Korst, J
Pauws, S
Keywords: artificial intelligence
cluster analysis
Publication Date: 2008
Abstract: Given a set of objects and their pairwise distances, we wish to determine a visual representation of the data. We use the quartet paradigm to compute a hierarchy of clusters of the objects. The method is based on an NP-hard graph optimization problem called the Minimum Quartet Tree Cost problem. This paper presents and compares several metaheuristic approaches to approximate the optimal hierarchy. The performance of the algorithms is tested through extensive computational experiments and it is shown that the Reduced Variable Neighbourhood Search metaheuristic is the most effective approach to the problem, obtaining high quality solutions in short computational running times.
Appears in Collections:School of Information Systems, Computing and Mathematics Research Papers
Mathematical Science
Computer Science

Files in This Item:

File Description SizeFormat
JOC_paper.pdf501.14 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.


Library (c) Brunel University.    Powered By: DSpace
Send us your
Feedback. Last Updated: September 14, 2010.
Managed by:
Hassan Bhuiyan