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.

• Type: Conference
• Year: 2005
• Where: ICML
• Authors: Thomas Finley, Thorsten Joachims
• Keywords: Clustering Algorithm, ICML 2005, Machine Learning, Noun-phrase Coreference Clustering, SVM Algorithm