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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2806

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
networks
graphs
heuristics
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.
URI: http://bura.brunel.ac.uk/handle/2438/2806
Appears in Collections:School of Information Systems, Computing and Mathematics Research Papers
Mathematical Science
Computer Science

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