Authors: Mladenović, Nenad 
Hansen, Pierre
Brimberg, Jack
Title: Sequential clustering with radius and split criteria
Journal: Central European Journal of Operations Research
Volume: 21
Issue: SUPPL1
First page: 95
Last page: 115
Issue Date: 1-Jun-2013
Rank: M23
ISSN: 1435-246X
DOI: 10.1007/s10100-012-0258-3
Abstract: 
Sequential clustering aims at determining homogeneous and/or well-separated clusters within a given set of entities, one at a time, until no more such clusters can be found. We consider a bi-criterion sequential clustering problem in which the radius of a cluster (or maximum dissimilarity between an entity chosen as center and any other entity of the cluster) is chosen as a homogeneity criterion and the split of a cluster (or minimum dissimilarity between an entity in the cluster and one outside of it) is chosen as a separation criterion. An O(N 3) algorithm is proposed for determining radii and splits of all efficient clusters, which leads to an O(N 4) algorithm for bi-criterion sequential clustering with radius and split as criteria. This algorithm is illustrated on the well known Ruspini data set.
Keywords: Clustering | Efficient cluster | Radius | Sequential | Split
Publisher: Springer Link

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