%0 Book Section %1 noKey %A Ruiz, Carlos %A Vallejo, CarlosG. %A Spiliopoulou, Myra %A Menasalvas, Ernestina %B Current Topics in Artificial Intelligence %D 2010 %E Meseguer, Pedro %E Mandow, Lawrence %E Gasca, RafaelM. %I Springer Berlin Heidelberg %K kmd %P 151-160 %R 10.1007/978-3-642-14264-2_16 %T Automated Constraint Selection for Semi-supervised Clustering Algorithm %U http://dx.doi.org/10.1007/978-3-642-14264-2_16 %V 5988 %X The incorporation of background knowledge in unsupervised algorithms has been shown to yield performance improvements in terms of model quality and execution speed. However, performance is dependent on the quantity and quality of the background knowledge being exploited. In this work, we study the issue of selecting Must-Link and Cannot-Link constraints for semi-supervised clustering. We propose “ %@ 978-3-642-14263-5

@incollection{noKey, abstract = {The incorporation of background knowledge in unsupervised algorithms has been shown to yield performance improvements in terms of model quality and execution speed. However, performance is dependent on the quantity and quality of the background knowledge being exploited. In this work, we study the issue of selecting Must-Link and Cannot-Link constraints for semi-supervised clustering. We propose “}, added-at = {2014-06-20T12:36:40.000+0200}, author = {Ruiz, Carlos and Vallejo, CarlosG. and Spiliopoulou, Myra and Menasalvas, Ernestina}, biburl = {https://www.bibsonomy.org/bibtex/266706309e17b5a41f2990fde591abb40/kmd-ovgu}, booktitle = {Current Topics in Artificial Intelligence}, doi = {10.1007/978-3-642-14264-2_16}, editor = {Meseguer, Pedro and Mandow, Lawrence and Gasca, RafaelM.}, interhash = {c6aeb5c90988e159563e9b51f883165f}, intrahash = {66706309e17b5a41f2990fde591abb40}, isbn = {978-3-642-14263-5}, keywords = {kmd}, language = {English}, pages = {151-160}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2014-06-20T12:36:40.000+0200}, title = {Automated Constraint Selection for Semi-supervised Clustering Algorithm}, url = {http://dx.doi.org/10.1007/978-3-642-14264-2_16}, volume = 5988, year = 2010 }