Matching person names through name transformation

TitleMatching person names through name transformation
Publication TypeConference Papers
Year of Publication2009
AuthorsGong J, Wang L, Oard D
Conference NameProceedings of the 18th ACM conference on Information and knowledge management
Date Published2009///
Conference LocationNew York, NY, USA
ISBN Number978-1-60558-512-3
Keywordsname matching, string distance metrics, string similarity

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.