Adaptive name matching in information integration

IEEE Intelligent Systems

Volumn 18, Issue 5, 2003, Pages 16-23

  Bilenko, Mikhail ^a,c   Mooney, Raymond ^a,c   Cohen, William ^b   Ravikumar, Pradeep ^b,d   Fienberg, Stephen ^b  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

^c University of Texas at Austin   (United States)

^d Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION INTEGRATION; NAME MATCHING;

DATA MINING; DATABASE SYSTEMS; DIGITAL LIBRARIES; DYNAMIC PROGRAMMING; MATRIX ALGEBRA; OPTICAL CHARACTER RECOGNITION; SET THEORY; WEBSITES;

INFORMATION ANALYSIS;

EID: 2342447399     PISSN: 10947167     EISSN: None     Source Type: Journal    
DOI: 10.1109/MIS.2003.1234765     Document Type: Article

References (12)

1. R. Durban et al., Biological Sequence Analysis-Probabilistic Models of Proteins and Nucleic Acids, Cambridge Univ. Press, 1998.
2. A. Monge and C. Elkan, "The Field-Matching Problem: Algorithm and Applications." Proc. 2nd ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, AAAI Press, 1996, pp. 267-270.
3. A. Monge and C. Elkan, "An Efficient Domain-Independent Algorithm for Detecting Approximately Duplicate Database Records," Proc. SIGMOD Workshop Data Mining and Knowledge Discovery, ACM Press, 1997, pp. 267-270.
4. M.A. Jaro, "Advances in Record-Linkage Methodology as Applied to Matching the 1985 Census of Tampa, Florida," J. Am. Statistical Assoc., vol. 84, no. 406, June 1989, pp. 414-420.
5. M.A. Jaro, "Probabilistic Linkage of Large Public Health Data Files," Statistics in Medicine, vol. 14, nos. 5-7, Mar./Apr. 1995, pp. 491-498.
6. W.E. Winkler, "The State of Record Linkage and Current Research Problems," Statistics of Income Division, Internal Revenue Service Publication R99/04, 1999; www.census. gov/srd/www/byname.html.
7. W.W. Cohen, "Data Integration Using Similarity Joins and a Word-Based Information Representation Language," ACM Trans. Information Systems, vol. 18, no. 3, July 2000, pp. 288-321.
8. S. Tejada, C.A. Knoblock, and S. Minton, "Learning Object Identification Rules for Information Integration," Information Systems, vol. 26, no. 8, Dec. 2001, pp. 607-633.
9. T. Joachims, Learning to Classify Text Using Support Vector Machines, Kluwer, 2002.
10. E.S. Ristad and P.M. Yianilos, "Learning String-Edit Distance," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 5, May 1998, pp. 522-532.
11. L.R. Rabiner, "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition," Proc. IEEE, vol. 77, no. 2, Feb. 1989, pp. 257-286.
12. M. Bilenko and R.J. Mooney, "Adaptive Duplicate Detection Using Learnable String Similarity Measures," Proc. 9th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD 2003), ACM Press, 2003, pp. 39-48.