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PKDD
2004
Springer

Combining Multiple Clustering Systems

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Combining Multiple Clustering Systems
Three methods for combining multiple clustering systems are presented and evaluated, focusing on the problem of finding the correspondence between clusters of different systems. In this work, the clusters of individual systems are represented in a common space and their correspondence estimated by either “clustering clusters” or with Singular Value Decomposition. The approaches are evaluated for the task of topic discovery on three major corpora and eight different clustering algorithms and it is shown experimentally that combination schemes almost always offer gains compared to single systems, but gains from using a combination scheme depend on the underlying clustering systems.
Constantinos Boulis, Mari Ostendorf
Added 02 Jul 2010
Updated 02 Jul 2010
Type Conference
Year 2004
Where PKDD
Authors Constantinos Boulis, Mari Ostendorf
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