U.S. flag

An official website of the United States government, Department of Justice.

NCJRS Virtual Library

The Virtual Library houses over 235,000 criminal justice resources, including all known OJP works.
Click here to search the NCJRS Virtual Library

Answer: Approximate Name Search with Errors in Large Databases by a Novel Approach Based on Prefix-dictionary

NCJ Number
International Journal on Artificial Intelligence Tools Volume: 15 Issue: 05 Dated: 2006 Pages: 839-848
Olcay Kursun; Anna Koufakou; Abhijit Wakchaure; Michael Georgiopoulos; Kenneth Reynolds; Ronald Eaglin
Date Published
10 pages

The authors propose and demonstrate the effectiveness of a name search with errors in large databases using a novel approach based on prefix-dictionary.


The obvious need for using modern computer networking capabilities to enable the effective sharing of information has resulted in data-sharing systems, which store, and manage large amounts of data. These data need to be effectively searched and analyzed. More specifically, in the presence of dirty data, a search for specific information by a standard query (e.g., search for a name that is misspelled or mistyped) does not return all needed information, as required in homeland security, criminology, and medical applications, amongst others. Different techniques, such as soundex, phonix, n-grams, edit-distance, have been used to improve the matching rate in these name-matching applications. These techniques have demonstrated varying levels of success, but there is a pressing need for name matching approaches that provide high levels of accuracy in matching names, while at the same time maintaining low computational complexity. In this paper, such a technique, called ANSWER, is proposed and its characteristics are discussed. The authors’ results demonstrate that ANSWER possesses high accuracy, as well as high speed and is superior to other techniques of retrieving fuzzy name matches in large databases. (Publisher abstract provided)