Internet Browsing and Searching: User Evaluation of Category Map and Concept Space Techniques
| dc.contributor.author | Chen, Hsinchun | |
| dc.contributor.author | Houston, Andrea L. | |
| dc.contributor.author | Sewell, Robin R. | |
| dc.contributor.author | Schatz, Bruce R. | |
| dc.date.accessioned | 2004-09-20T00:00:01Z | |
| dc.date.available | 2010-06-18T23:19:43Z | |
| dc.date.issued | 1998 | en_US |
| dc.date.submitted | 2004-09-20 | en_US |
| dc.identifier.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 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/105118 | |
| dc.description | Artificial Intelligence Lab, Department of MIS, University of Arizona | en_US |
| dc.description.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. | |
| dc.format.mimetype | application/pdf | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Wiley Periodicals, Inc | en_US |
| dc.subject | Internet | en_US |
| dc.subject | Information Seeking Behaviors | en_US |
| dc.subject.other | National Science Digital Library | en_US |
| dc.subject.other | NSDL | en_US |
| dc.subject.other | Artificial Intelligence lab | en_US |
| dc.subject.other | AI lab | en_US |
| dc.subject.other | SOM | en_US |
| dc.title | Internet Browsing and Searching: User Evaluation of Category Map and Concept Space Techniques | en_US |
| dc.type | Journal Article (Paginated) | en_US |
| dc.identifier.journal | Journal of the American Society for Information Science, Special Issue on AI Techniques for Emerging Information Systems Applications | en_US |
| refterms.dateFOA | 2018-08-21T10:10:06Z | |
| html.description.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. |
