By Topic

Approximate string joins

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Srivastava, D. ; AT/spl and/T Labs-Res., Florham Park, NJ, USA

Summary form only given. String data is ubiquitous and is commonly used to correlate (or join) entities across autonomous, heterogeneous databases. The main challenge is to effectively deal with the noisy nature of string data, due to, for example, transcription errors, incomplete information, and multiple conventions for recording string value attributes. Commercial databases do not support approximate string joins directly, and it is a challenge to implement this functionality efficiently. The author presents techniques for performing approximate string joins, based n a variety of string similarity metrics, including variants of edit distance and cosine similarity. These techniques are scalable, and can be formulated to execute efficiently in a relational database management system.

Published in:

Scientific and Statistical Database Management, 2003. 15th International Conference on

Date of Conference:

9-11 July 2003