A Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System

Persistent Link:
http://hdl.handle.net/10150/105991
Title:
A Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System
Author:
Chen, Hsinchun; Martinez, Joanne; Ng, Tobun Dorbin; Schatz, Bruce R.
Citation:
A Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System 1997-01, 48(1):17-31 Journal of the American Society for Information Science
Publisher:
Wiley Periodicals, Inc
Journal:
Journal of the American Society for Information Science
Issue Date:
Jan-1997
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105991
Submitted date:
2004-10-01
Abstract:
This research presents an algorithmic approach to addressing the vocabulary problem in scientific information retrieval and information sharing, using the molecular biology domain as an example. We first present a literature review of cognitive studies related to the vocabulary problem and vocabuiary-based search aids (thesauri) and then discuss techniques for building robust and domain-specific thesauri to assist in cross-domain scientific information retrieval. Using a variation of the automatic thesaurus generation techniques, which we refer to as the concept space approach, we recently conducted an experiment in the molecular biology domain in which we created a C. elegans worm thesaurus of 7,657 worm-specific terms and a Drosofila fly thesaurus of 15,626 terms. About 30% of these terms overlapped, which created vocabulary paths from one subject domain to the other. Based on a cognitive study of term association involving four biologists, we found that a large percentage (59.6-85.6%) of the terms suggested by the subjects were identified in the conjoined fly-worm thesaurus. However, we found only a small percentage (8.4-18.1%) of the associations suggested by the subjects in the thesaurus. In a follow-up document retrieval study involving eight fly biologists, an actual worm database (Worm Community System), and the conjoined flyworm thesaurus, subjects were able to find more relevant documents (an increase from about 9 documents to 20) and to improve the document recall level (from 32.41 to 65.28%) when using the thesaurus, although the precision level did not improve significantly. Implications of adopting the concept space approach for addressing the vocabulary problem in Internet and digital libraries applications are also discussed.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Geographic Information Science; Information Extraction
Local subject classification:
National Science Digital Library; NSDL; Artificial intelligence lab; AI lab; Information retrieval

Full metadata record

DC FieldValue Language
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorMartinez, Joanneen_US
dc.contributor.authorNg, Tobun Dorbinen_US
dc.contributor.authorSchatz, Bruce R.en_US
dc.date.accessioned2004-10-01T00:00:01Z-
dc.date.available2010-06-18T23:37:51Z-
dc.date.issued1997-01en_US
dc.date.submitted2004-10-01en_US
dc.identifier.citationA Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community System 1997-01, 48(1):17-31 Journal of the American Society for Information Scienceen_US
dc.identifier.urihttp://hdl.handle.net/10150/105991-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractThis research presents an algorithmic approach to addressing the vocabulary problem in scientific information retrieval and information sharing, using the molecular biology domain as an example. We first present a literature review of cognitive studies related to the vocabulary problem and vocabuiary-based search aids (thesauri) and then discuss techniques for building robust and domain-specific thesauri to assist in cross-domain scientific information retrieval. Using a variation of the automatic thesaurus generation techniques, which we refer to as the concept space approach, we recently conducted an experiment in the molecular biology domain in which we created a C. elegans worm thesaurus of 7,657 worm-specific terms and a Drosofila fly thesaurus of 15,626 terms. About 30% of these terms overlapped, which created vocabulary paths from one subject domain to the other. Based on a cognitive study of term association involving four biologists, we found that a large percentage (59.6-85.6%) of the terms suggested by the subjects were identified in the conjoined fly-worm thesaurus. However, we found only a small percentage (8.4-18.1%) of the associations suggested by the subjects in the thesaurus. In a follow-up document retrieval study involving eight fly biologists, an actual worm database (Worm Community System), and the conjoined flyworm thesaurus, subjects were able to find more relevant documents (an increase from about 9 documents to 20) and to improve the document recall level (from 32.41 to 65.28%) when using the thesaurus, although the precision level did not improve significantly. Implications of adopting the concept space approach for addressing the vocabulary problem in Internet and digital libraries applications are also discussed.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherWiley Periodicals, Incen_US
dc.subjectGeographic Information Scienceen_US
dc.subjectInformation Extractionen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherInformation retrievalen_US
dc.titleA Concept Space Approach to Addressing the Vocabulary Problem in Scientific Information Retrieval: An Experiment on the Worm Community Systemen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalJournal of the American Society for Information Scienceen_US
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