A Path to Concept-based Information Access: From National Collaboratories to Digital Libraries

Persistent Link:
http://hdl.handle.net/10150/105696
Title:
A Path to Concept-based Information Access: From National Collaboratories to Digital Libraries
Author:
Houston, Andrea L.; Chen, Hsinchun
Editors:
Olson, G.M.; Malone, T.W.; Smith, J.B.
Citation:
A Path to Concept-based Information Access: From National Collaboratories to Digital Libraries 2000, :739-760 Coordination Theory and Collaboration Technology
Publisher:
Lawrence Eribaum Associates
Journal:
Coordination Theory and Collaboration Technology
Issue Date:
2000
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105696
Submitted date:
2004-10-01
Abstract:
This research aims to provide a semantic, concept-based retrieval option that could supplement existing information retrieval options. Our proposed approach is based on textual analysis of a large corpus of domain-specific documents in order to generate a large set of subject vocabularies. By adopting cluster analysis techniques to analyze the co-occurrence probabilities of the subject vocabularies, a similarity matrix of vocabularies can be built to represent the important concepts and their weighted “relevance” relationships in the subject domain. To create a network of concepts, which we refer to as the “concept space” for the subject domain, we propose to develop general AI-based graph traversal algorithms and graph matching algorithms to automatically translate a searcher’ s preferred vocabularies into a set of the most semantically relevant terms in the database’s underlying subject domain. By providing a more understandable, system-generated, semantics-rich concept space plus algorithms to assist in concept/information spaces traversal, we believe we can greatly alleviate both information overload and the vocabulary problem. In this chapter, we first review our concept space approach and the associated algorithms in Section 2. In Section 3, we describe our experience in using such an approach. In Section 4, we summarize our research findings and our plan for building a semantics-rich Interspace for the Illinois Digital Library project.
Type:
Book Chapter
Language:
en
Keywords:
Digital Libraries; 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.authorHouston, Andrea L.en_US
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.editorOlson, G.M.en_US
dc.contributor.editorMalone, T.W.en_US
dc.contributor.editorSmith, J.B.en_US
dc.date.accessioned2004-10-01T00:00:01Z-
dc.date.available2010-06-18T23:31:59Z-
dc.date.issued2000en_US
dc.date.submitted2004-10-01en_US
dc.identifier.citationA Path to Concept-based Information Access: From National Collaboratories to Digital Libraries 2000, :739-760 Coordination Theory and Collaboration Technologyen_US
dc.identifier.urihttp://hdl.handle.net/10150/105696-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractThis research aims to provide a semantic, concept-based retrieval option that could supplement existing information retrieval options. Our proposed approach is based on textual analysis of a large corpus of domain-specific documents in order to generate a large set of subject vocabularies. By adopting cluster analysis techniques to analyze the co-occurrence probabilities of the subject vocabularies, a similarity matrix of vocabularies can be built to represent the important concepts and their weighted “relevance” relationships in the subject domain. To create a network of concepts, which we refer to as the “concept space” for the subject domain, we propose to develop general AI-based graph traversal algorithms and graph matching algorithms to automatically translate a searcher’ s preferred vocabularies into a set of the most semantically relevant terms in the database’s underlying subject domain. By providing a more understandable, system-generated, semantics-rich concept space plus algorithms to assist in concept/information spaces traversal, we believe we can greatly alleviate both information overload and the vocabulary problem. In this chapter, we first review our concept space approach and the associated algorithms in Section 2. In Section 3, we describe our experience in using such an approach. In Section 4, we summarize our research findings and our plan for building a semantics-rich Interspace for the Illinois Digital Library project.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherLawrence Eribaum Associatesen_US
dc.subjectDigital Librariesen_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 Path to Concept-based Information Access: From National Collaboratories to Digital Librariesen_US
dc.typeBook Chapteren_US
dc.identifier.journalCoordination Theory and Collaboration Technologyen_US
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