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Adaptive Name Matching in Information Integration
September/October 2003 (vol. 18 no. 5)
pp. 16-23
Mikhail Bilenko, University of Texas at Austin
Raymond Mooney, University of Texas at Austin
William Cohen, Carnegie Mellon University
Pradeep Ravikumar, Carnegie Mellon University
Stephen Fienberg, Carnegie Mellon University

Identifying approximately duplicate database records that refer to the same entity is essential for information integration. The authors review traditional approaches to solving this problem and present their recent experimental results on comparing, combining, and learning textual similarity measures for name matching.

Index Terms:
database integration, text mining, machine learning, similarity measures
Citation:
Mikhail Bilenko, Raymond Mooney, William Cohen, Pradeep Ravikumar, Stephen Fienberg, "Adaptive Name Matching in Information Integration," IEEE Intelligent Systems, vol. 18, no. 5, pp. 16-23, Sept.-Oct. 2003, doi:10.1109/MIS.2003.1234765
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