An efficient divisive-agglomerative hierarchical clustering algorithm using minimum spanning tree

Many systems in Science and Engineering can be modeled as graph. Clustering is a process of discovering group of objects such that the objects of the same group are similar, and objects belonging to different groups are dissimilar. A number of clustering algorithms exist that can solve the problem o...

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Veröffentlicht in:Journal of discrete mathematical sciences & cryptography Jg. 14; H. 6; S. 583 - 595
Hauptverfasser: Peter, S. John, Chidambaranathan, S.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Taylor & Francis Group 01.12.2011
Schlagworte:
Algorithms
Boundaries
Clustering
Clusters
Cryptography
edge structure
Euclidean minimum spanning tree
Graph theory
Graphs
Mathematical models
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ISSN:0972-0529, 2169-0065
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Zusammenfassung:Many systems in Science and Engineering can be modeled as graph. Clustering is a process of discovering group of objects such that the objects of the same group are similar, and objects belonging to different groups are dissimilar. A number of clustering algorithms exist that can solve the problem of clustering, but most of them are very sensitive to their input parameters. Graph based clustering algorithms aimed to find hidden structures from objects. Minimum Spanning Tree clustering algorithm is capable of detecting clusters with irregular boundaries. In this paper we present a new clustering algorithm using Minimum Spanning Tree. The newly proposed algorithm can find hierarchical structure of clusters without requiring any input parameters. The experiment using synthetic data demonstrates the performance of new algorithm.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:0972-0529
2169-0065
DOI:10.1080/09720529.2011.10698357