Heuristic Approaches for the Quartet Method of Hierarchical Clustering

Sergio Consoli; Kenneth Darby-Dowman; Gijs Geleijnse; Jan Korst; Steffen Pauws

doi:10.1109/TKDE.2009.188

Heuristic Approaches for the Quartet Method of Hierarchical Clustering

Sergio Consoli^*, Kenneth Darby-Dowman, Gijs Geleijnse, Jan Korst, Steffen Pauws

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

16 Citations (Scopus)

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 heuristic 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 Neighborhood Search heuristic is the most effective approach to the problem, obtaining high-quality solutions in short computational running times.

Original language	English
Pages (from-to)	1428-1443
Number of pages	16
Journal	IEEE Transactions on Knowledge and Data Engineering
Volume	22
Issue number	10
DOIs	https://doi.org/10.1109/TKDE.2009.188
Publication status	Published - Oct 2010
Externally published	Yes

Keywords

Clustering
heuristic methods
optimization
graphs and networks
EVOLUTIONARY TREES
PHYLOGENIES
TOPOLOGIES

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10.1109/TKDE.2009.188

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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 heuristic 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 Neighborhood Search heuristic is the most effective approach to the problem, obtaining high-quality solutions in short computational running times.",

keywords = "Clustering, heuristic methods, optimization, graphs and networks, EVOLUTIONARY TREES, PHYLOGENIES, TOPOLOGIES",

author = "Sergio Consoli and Kenneth Darby-Dowman and Gijs Geleijnse and Jan Korst and Steffen Pauws",

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AU - Darby-Dowman, Kenneth

AU - Geleijnse, Gijs

AU - Korst, Jan

AU - Pauws, Steffen

PY - 2010/10

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KW - Clustering

KW - heuristic methods

KW - optimization

KW - graphs and networks

KW - EVOLUTIONARY TREES

KW - PHYLOGENIES

KW - TOPOLOGIES

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JO - IEEE Transactions on Knowledge and Data Engineering

JF - IEEE Transactions on Knowledge and Data Engineering

IS - 10

ER -

Heuristic Approaches for the Quartet Method of Hierarchical Clustering

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Keywords

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