A Dictionary-Based Approach to Fast and Accurate Name Matching in Large Law Enforcement Databases

  • Olcay Kursun
  • Anna Koufakou
  • Bing Chen
  • Michael Georgiopoulos
  • Kenneth M. Reynolds
  • Ron Eaglin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3975)


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. This is an issue of grave importance in homeland security, criminology, medical applications, GIS (geographic information systems) and so on. Different techniques, such as soundex, phonix, n-grams, edit-distance, have been used to improve the matching rate in these name-matching applications. There is a pressing need for name matching approaches that provide high levels of accuracy, while at the same time maintaining the computational complexity of achieving this goal reasonably low. In this paper, we present ANSWER, a name matching approach that utilizes a prefix-tree of available names in the database. Creating and searching the name dictionary tree is fast and accurate and, thus, ANSWER is superior to other techniques of retrieving fuzzy name matches in large databases.


Edit Distance Recall Rate Homeland Security Geographic Information System Match Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Olcay Kursun
    • 1
  • Anna Koufakou
    • 2
  • Bing Chen
    • 2
  • Michael Georgiopoulos
    • 2
  • Kenneth M. Reynolds
    • 3
  • Ron Eaglin
    • 1
  1. 1.Department of Engineering TechnologyUniversity of Central FloridaOrlando
  2. 2.School of Electrical Engineering and Computer ScienceUniversity of Central FloridaOrlando
  3. 3.Department of Criminal Justice and Legal StudiesUniversity of Central FloridaOrlando

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