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ICML
2005
IEEE

Supervised clustering with support vector machines

14 years 4 months ago
Supervised clustering with support vector machines
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn how to cluster future sets of items. Example applications include noun-phrase coreference clustering, and clustering news articles by whether they refer to the same topic. In this paper we present an SVM algorithm that trains a clustering algorithm by adapting the item-pair similarity measure. The algorithm may optimize a variety of different clustering functions to a variety of clustering performance measures. We empirically evaluate the algorithm for noun-phrase and news article clustering.
Thomas Finley, Thorsten Joachims
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2005
Where ICML
Authors Thomas Finley, Thorsten Joachims
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