Title

Name Matching In Law Enforcement Database

Abstract

As it is the case with all database systems that collect and store data, data input errors occur resulting in less than perfect data integrity, or what is common referred to as the "dirtydata" problem. American investigators are not familiar with many foreign names such as Zacarias Moussaoui. If the first or last name is spelled incorrectly during a query, the person record could be missed. Individuals who are chronic offenders and those who are attempting to evade detection use alias. Moussaoui is also known as Shaqil and Abu Khalid al Sahrawi. Unless smart analytical tools are available for effective name matching where data integrity conditions, challenging name spellings, and deliberate obfuscation are present, the likelihood of missing a critical record is high. This paper addresses some of the problems stemming from unreliable and inaccurate law enforcement data. Although the ideas proposed are using " name data" as an illustration of how to deal with dirty data, the proposed approaches will be extended to other types of dirty data in the law enforcement databases, such as addresses, stolen item/article names/descriptions/brand names, etc. © 2008 Springer-Verlag Berlin Heidelberg.

Publication Date

7-3-2008

Publication Title

Studies in Computational Intelligence

Volume

135

Number of Pages

151-172

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-540-69209-6_9

Socpus ID

45949099451 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/45949099451

This document is currently not available here.

Share

COinS