Abstract
The default pattern matching capabilities in today’s RDBMS are generally unable to cope with errors and variations that may exist in stored textual information. In this paper, we present SKIPPER, a simple search methodology that allows approximate string matching on multiple-attribute, large-scale customer address information for the Credit Collection industry. The proposed solution relies on the edit distance error model and the q-gram string filtering technique. We present an algorithm that integrates the methodology with existing RDBMS through SQL-based stored procedures.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Gravano, L., Ipeirotis, P.G., Jagadish, H.V., Koudas, N., Muthukrishnan, S., Pietarinen, L., Srivastava, D.: Using q-grams in a DBMS for Approximate String Processing. IEEE Data Engineering Bulletin 24(4), 28–34 (2001)
Gravano, L., Ipeirotis, P.G., Jagadish, H.V., Koudas, N., Muthukrishnan, S., Srivastava, D.: Approximate string joins in a database (almost) for free. In: Proceedings of the 27th International Conference on Very Large Databases (VLDB 2001), pp. 491–500 (2001)
Ristad, E.S., Yianilos, P.Y.: Learning String Edit Distance, Research Report CS-TR- 532-96, Dept. of Computer Science, Princeton University (1997)
Winkler, W.E.: The State of Record Linkage and Current Research Problems, Technical report, Statistical Research Division, U.S. Bureau of the Census, Washington, D.C (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cheong, Y.M., Tay, J.C. (2003). Approximate String Matching for Multiple-Attribute, Large-Scale Customer Address Databases. In: Sembok, T.M.T., Zaman, H.B., Chen, H., Urs, S.R., Myaeng, SH. (eds) Digital Libraries: Technology and Management of Indigenous Knowledge for Global Access. ICADL 2003. Lecture Notes in Computer Science, vol 2911. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24594-0_16
Download citation
DOI: https://doi.org/10.1007/978-3-540-24594-0_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20608-8
Online ISBN: 978-3-540-24594-0
eBook Packages: Springer Book Archive