Internet Browsing and Searching: User Evaluation of Category Map and Concept Space Techniques

Persistent Link:
http://hdl.handle.net/10150/105118
Title:
Internet Browsing and Searching: User Evaluation of Category Map and Concept Space Techniques
Author:
Chen, Hsinchun; Houston, Andrea L.; Sewell, Robin R.; Schatz, Bruce R.
Citation:
Internet Browsing and Searching: User Evaluation of Category Map and Concept Space Techniques 1998, 49(7):582-603 Journal of the American Society for Information Science, Special Issue on AI Techniques for Emerging Information Systems Applications
Publisher:
Wiley Periodicals, Inc
Journal:
Journal of the American Society for Information Science, Special Issue on AI Techniques for Emerging Information Systems Applications
Issue Date:
1998
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105118
Submitted date:
2004-09-20
Abstract:
Research was focused on discovering whether two of the algorithms the research group has developed can help improve browsing and/or searching the Internet. Results indicate that a Kohonen self-organizing map (SOM)-based algorithm can successfully categorize a large and eclectic Internet information space into managable sub-spaces that users can successfully navigate to locate a homepage of interest to them.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Internet; Information Seeking Behaviors
Local subject classification:
National Science Digital Library; NSDL; Artificial Intelligence lab; AI lab; SOM

Full metadata record

DC FieldValue Language
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorHouston, Andrea L.en_US
dc.contributor.authorSewell, Robin R.en_US
dc.contributor.authorSchatz, Bruce R.en_US
dc.date.accessioned2004-09-20T00:00:01Z-
dc.date.available2010-06-18T23:19:43Z-
dc.date.issued1998en_US
dc.date.submitted2004-09-20en_US
dc.identifier.citationInternet Browsing and Searching: User Evaluation of Category Map and Concept Space Techniques 1998, 49(7):582-603 Journal of the American Society for Information Science, Special Issue on AI Techniques for Emerging Information Systems Applicationsen_US
dc.identifier.urihttp://hdl.handle.net/10150/105118-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractResearch was focused on discovering whether two of the algorithms the research group has developed can help improve browsing and/or searching the Internet. Results indicate that a Kohonen self-organizing map (SOM)-based algorithm can successfully categorize a large and eclectic Internet information space into managable sub-spaces that users can successfully navigate to locate a homepage of interest to them.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherWiley Periodicals, Incen_US
dc.subjectInterneten_US
dc.subjectInformation Seeking Behaviorsen_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.otherSOMen_US
dc.titleInternet Browsing and Searching: User Evaluation of Category Map and Concept Space Techniquesen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalJournal of the American Society for Information Science, Special Issue on AI Techniques for Emerging Information Systems Applicationsen_US
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