@conference {15896,
	title = {Matching person names through name transformation},
	booktitle = {Proceedings of the 18th ACM conference on Information and knowledge management},
	series = {CIKM {\textquoteright}09},
	year = {2009},
	month = {2009///},
	pages = {1875 - 1878},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Matching person names plays an important role in many applications, including bibliographic databases and indexing systems. Name variations and spelling errors make exact string matching problematic; therefore, it is useful to develop methodologies that can handle variant forms for the same named entity. In this paper, a novel person name matching model is presented. Common name variations in the English speaking world are formalized, and the concept of name transformation paths is introduced; name similarity is measured after the best transformation path has been selected. Supervised techniques are used to learn a similarity function and a decision rule. Experiments with three datasets show the method to be effective.},
	keywords = {name matching, string distance metrics, string similarity},
	isbn = {978-1-60558-512-3},
	doi = {10.1145/1645953.1646253},
	url = {http://doi.acm.org/10.1145/1645953.1646253},
	author = {Gong,Jun and Wang,Lidan and Oard, Douglas}
}
