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Journal of Information Science
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A hybrid approach to fuzzy name search incorporating language-based and text-based principles

Paul Wu Horng-Jyh

Nanyang Technological University, 31 Nanyang Link, Singapore 637718, hjwu{at}ntu.edu.sg

Na Jin-Cheon

Nanyang Technological University, 31 Nanyang Link, Singapore 637718

Christopher Khoo Soo-Guan

Nanyang Technological University, 31 Nanyang Link, Singapore 637718

Name Search is an important search function in various types of information retrieval systems, such as online library catalogs and electronic yellow pages. It is also difficult, because of the high degree of fuzziness required in matching name variants. Previous approaches to name search systems use ad hoc combinations of search heuristics. This paper first discusses two approaches to name modeling - the natural language processing (NLP) and information retrieval (IR) models - and proposes a hybrid approach. The approach demonstrates a critical combination of complementary NLP and IR features that produces more effective fuzzy name matching. Two principles, position-as-attribute and position-transition-likelihood , are introduced as the principles for integrating the advantageous aspects of both approaches. They have been implemented in an NLP- and IR-hybrid model system called Friendly Name Search (FNS) for real world applications in multilingual directory searches on the Singapore Yellow pages website.

Key Words: fuzzy name search • natural language processing • information retrieval • hybrid system • language and text

Journal of Information Science, Vol. 33, No. 1, 3-19 (2007)
DOI: 10.1177/0165551506068146
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