Year: 1988
Type: conference-paper
Abstract: This paper describes enhancements made to techniques currently used to search large databases of proper names. Improvements included use of a Hidden Markov Model (HMM) statistical classifier to identify the likely linguistic provenance of a surname, and application of language-specific rules to generate plausible spelling variations of names. These two components were incorporated into a prototype front-end system driving existing name search procedures. HMM models and sets of linguistic rules were constructed for Farsi, Spanish and Vietnamese surnames and tested on a database of over 11,000 entries. Preliminary evaluation indicates improved retrieval of 20--30% as measured by number of correct items retrieved.
Authors: Beatrice T. Oshika, Bruce Evans, Filip Machi, Janet Tom
Institutions: University of California, Berkeley, Unisys (United States)
Language: English
Topic: Data Quality and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: bronze
OpenAlex ID: W2006807136