Automatic training example selection for scalable unsupervised record linkage

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5012 LNAI, Issue , 2008, Pages 511-518

  Christen, Peter ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

Clustering; Data linkage; Data mining preprocessing; Entity resolution; Support vector machines

Indexed keywords

AUTOMATIC PROGRAMMING; BINARY DECISION DIAGRAMS; CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; DATA MINING; SUPPORT VECTOR MACHINES;

DATA LINKAGE; DATA MINING PREPROCESSING; ENTITY RESOLUTION; K-MEANS CLUSTERING;

UNSUPERVISED LEARNING;

EID: 44649093306     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-68125-0_45     Document Type: Conference Paper

References (13)

1. Baxter, R., Christen, P., Churches, T.: A comparison of fast blocking methods for record linkage. In: ACM KDD 2003 workshop on Data Cleaning, Record Linkage and Object Consolidation, Washington DC, pp. 25-27 (2003)
2. Bilenko, M., Mooney, R.J.: Adaptive duplicate detection using learnable string similarity measures. In: ACM KDD 2003, Washington DC, pp. 39-48 (2003)
3. Chang, C.-C., Lin, C.-J.: LIBSVM: A library for support vector machines. Manual, Department of Computer Science, National Taiwan University (2001)
4. Christen, P.: Probabilistic data generation for deduplication and data linkage. In: Gallagher, M., Hogan, J.P., Maire, F. (eds.) IDEAL 2005. LNCS, vol. 3578, pp. 109-116. Springer, Heidelberg (2005)
5. Christen, P.: A two-step classification approach to unsupervised record linkage. In: AusDM 2007, CRPIT, Gold Coast, Australia, vol. 70 (2007)
6. Christen, P.: Febrl - a freely available record linkage system with a graphical user interface. In: HDKM 2008, CRPIT, Wollongong, Australia, vol. 80 (2008)
7. Christen, P., Goiser, K.: Quality and complexity measures for data linkage and deduplication. In: Quality Measures in Data Mining. Studies in Computational Intelligence, vol. 43, pp. 127-151. Springer, Heidelberg (2007)
8. Elfeky, M.G., Verykios, V.S., Elmagarmid, A.K.: TAILOR: A record linkage toolbox. In: ICDE 2002, San Jose, pp. 17-28 (2002)
9. Liu, B., Lee, W.S., Yu, P.S., Li, X.: Partially supervised classification of text documents. In: ICML 2002, Sydney, Australia, pp. 387-394 (2002)
10. Nahm, U.Y., Bilenko, M., Mooney, R,.J.: Two approaches to handling noisy variation in text mining. In: TextML 2002, Sydney, pp. 18-27 (2002)
11. Tejada, S., Knoblock, C.A., Minton, S.: Learning domain-independent string transformation weights for high accuracy object identification. In: ACM KDD 2002, Edmonton, pp. 350-359 (2002)
12. Winkler, W.E.: Methods for evaluating and creating data quality. Elsevier Information Systems 29(7), 531-550 (2004)
13. Yu, H., Han, J., Chang, K.C.C.: PEBL: positive example based learning for Web page classification using SVM. In: ACM KDD 2002, Edmonton (2002)