%0 Conference Paper %1 finley2005supervised %A Finley, Thomas %A Joachims, Thorsten %B Proceedings of the 22Nd International Conference on Machine Learning %C New York, NY, USA %D 2005 %I ACM %K clustering learning supervised svm %P 217--224 %R 10.1145/1102351.1102379 %T Supervised Clustering with Support Vector Machines %U http://doi.acm.org/10.1145/1102351.1102379 %X 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. %@ 1-59593-180-5

@inproceedings{finley2005supervised, abstract = {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.}, acmid = {1102379}, added-at = {2014-02-27T08:25:14.000+0100}, address = {New York, NY, USA}, author = {Finley, Thomas and Joachims, Thorsten}, biburl = {https://www.bibsonomy.org/bibtex/2d9a751001556c7e0a4226c85a6953a14/jaeschke}, booktitle = {Proceedings of the 22Nd International Conference on Machine Learning}, doi = {10.1145/1102351.1102379}, interhash = {e38b83deb235bfb47bef7add52607262}, intrahash = {d9a751001556c7e0a4226c85a6953a14}, isbn = {1-59593-180-5}, keywords = {clustering learning supervised svm}, location = {Bonn, Germany}, numpages = {8}, pages = {217--224}, publisher = {ACM}, series = {ICML '05}, timestamp = {2014-07-28T15:57:31.000+0200}, title = {Supervised Clustering with Support Vector Machines}, url = {http://doi.acm.org/10.1145/1102351.1102379}, year = 2005 }