%0 Conference Paper %B Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval %D 2009 %T Selecting hierarchical clustering cut points for web person-name disambiguation %A Gong,Jun %A Oard, Douglas %K clustering %K person-name disambiguation %X Hierarchical clustering is often used to cluster person-names referring to the same entities. Since the correct number of clusters for a given person-name is not known a priori, some way of deciding where to cut the resulting dendrogram to balance risks of over- or under-clustering is needed. This paper reports on experiments in which outcome-specific and result-set measures are used to learn a global similarity threshold. Results on the Web People Search (WePS)-2 task indicate that approximately 85% of the optimal F1 measure can be achieved on held-out data. %B Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval %S SIGIR '09 %I ACM %C New York, NY, USA %P 778 - 779 %8 2009/// %@ 978-1-60558-483-6 %G eng %U http://doi.acm.org/10.1145/1571941.1572124 %R 10.1145/1571941.1572124