A hybrid approach to fuzzy name search incorporating language-based and textbased principles

Persistent Link:
http://hdl.handle.net/10150/105835
Title:
A hybrid approach to fuzzy name search incorporating language-based and textbased principles
Author:
Wu, Paul Horng Jyh; Na, Jin Cheon; Khoo, Christopher S.G.
Citation:
A hybrid approach to fuzzy name search incorporating language-based and textbased principles 2007, 33(1) Journal of Information Science
Publisher:
SAGE Publications
Journal:
Journal of Information Science
Issue Date:
2007
URI:
http://hdl.handle.net/10150/105835
Submitted date:
2006-07-10
Abstract:
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 due to 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 modelingâ the natural language processing (NLP) and the information retrieval (IR) modelsâ 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-transitionlikelihood, 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.
Type:
Journal Article (On-line/Unpaginated)
Language:
en
Keywords:
Information Retrieval; Natural Language Processing
Local subject classification:
fuzzy name search; natural language processing; information retrieval; hybrid system; language and text

Full metadata record

DC FieldValue Language
dc.contributor.authorWu, Paul Horng Jyhen_US
dc.contributor.authorNa, Jin Cheonen_US
dc.contributor.authorKhoo, Christopher S.G.en_US
dc.date.accessioned2006-07-10T00:00:01Z-
dc.date.available2010-06-18T23:35:15Z-
dc.date.issued2007en_US
dc.date.submitted2006-07-10en_US
dc.identifier.citationA hybrid approach to fuzzy name search incorporating language-based and textbased principles 2007, 33(1) Journal of Information Scienceen_US
dc.identifier.urihttp://hdl.handle.net/10150/105835-
dc.description.abstractName 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 due to 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 modelingâ the natural language processing (NLP) and the information retrieval (IR) modelsâ 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-transitionlikelihood, 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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherSAGE Publicationsen_US
dc.subjectInformation Retrievalen_US
dc.subjectNatural Language Processingen_US
dc.subject.otherfuzzy name searchen_US
dc.subject.othernatural language processingen_US
dc.subject.otherinformation retrievalen_US
dc.subject.otherhybrid systemen_US
dc.subject.otherlanguage and texten_US
dc.titleA hybrid approach to fuzzy name search incorporating language-based and textbased principlesen_US
dc.typeJournal Article (On-line/Unpaginated)en_US
dc.identifier.journalJournal of Information Scienceen_US
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