Persistent Link:
http://hdl.handle.net/10150/105957
Title:
Internet Categorization and Search: A Self-Organizing Approach
Author:
Chen, Hsinchun; Schuffels, Chris; Orwig, Richard E.
Citation:
Internet Categorization and Search: A Self-Organizing Approach 1996, 7(1):88-102 Journal of Visual Communication and Image Representation, Special Issue on Digital Libraries
Publisher:
Academic Press, Inc.
Journal:
Journal of Visual Communication and Image Representation, Special Issue on Digital Libraries
Issue Date:
1996
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105957
Submitted date:
2004-09-20
Abstract:
The problems of information overload and vocabulary differences have become more pressing with the emergence of increasingly popular Internet services. The main information retrieval mechanisms provided by the prevailing Internet WWW software are based on either keyword search (e.g., the Lycos server at CMU, the Yahoo server at Stanford) or hypertext browsing (e.g., Mosaic and Netscape). This research aims to provide an alternative concept-based categorization and search capability for WWW servers based on selected machine learning algorithms. Our proposed approach, which is grounded on automatic textual analysis of Internet documents (homepages), attempts to address the Internet search problem by first categorizing the content of Internet documents. We report results of our recent testing of a multilayered neural network clustering algorithm employing the Kohonen self-organizing feature map to categorize (classify) Internet homepages according to their content. The category hierarchies created could serve to partition the vast Internet services into subject-specific categories and databases and improve Internet keyword searching and/or browsing.
Type:
Journal Article (Paginated)
Language:
en
Keywords:
Internet; Information Seeking Behaviors; 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.authorSchuffels, Chrisen_US
dc.contributor.authorOrwig, Richard E.en_US
dc.date.accessioned2004-09-20T00:00:01Z-
dc.date.available2010-06-18T23:37:21Z-
dc.date.issued1996en_US
dc.date.submitted2004-09-20en_US
dc.identifier.citationInternet Categorization and Search: A Self-Organizing Approach 1996, 7(1):88-102 Journal of Visual Communication and Image Representation, Special Issue on Digital Librariesen_US
dc.identifier.urihttp://hdl.handle.net/10150/105957-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractThe problems of information overload and vocabulary differences have become more pressing with the emergence of increasingly popular Internet services. The main information retrieval mechanisms provided by the prevailing Internet WWW software are based on either keyword search (e.g., the Lycos server at CMU, the Yahoo server at Stanford) or hypertext browsing (e.g., Mosaic and Netscape). This research aims to provide an alternative concept-based categorization and search capability for WWW servers based on selected machine learning algorithms. Our proposed approach, which is grounded on automatic textual analysis of Internet documents (homepages), attempts to address the Internet search problem by first categorizing the content of Internet documents. We report results of our recent testing of a multilayered neural network clustering algorithm employing the Kohonen self-organizing feature map to categorize (classify) Internet homepages according to their content. The category hierarchies created could serve to partition the vast Internet services into subject-specific categories and databases and improve Internet keyword searching and/or browsing.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherAcademic Press, Inc.en_US
dc.subjectInterneten_US
dc.subjectInformation Seeking Behaviorsen_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.titleInternet Categorization and Search: A Self-Organizing Approachen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalJournal of Visual Communication and Image Representation, Special Issue on Digital Librariesen_US
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