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HYPERTEXT BROWSING A NEW MODEL FOR INFORMATION FILTERING BASED ON USER PROFILES AND DATA CLUSTERING

HYPERTEXT BROWSING A NEW MODEL FOR INFORMATION FILTERING BASED ON USER PROFILES AND DATA CLUSTERING Hypertext users often experience the lost in hyperspace problem. This study suggests a solution which restricts the amount of information made available to the user, thus allowing improved hypertext browsing. An algorithm calculates the set of most relevant hypertext nodes for the user, utilising the user profile and data clustering technique. The result is an optimal cluster of relevant data items, customtailored for each user's needs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Online and CD-Rom Review Emerald Publishing

HYPERTEXT BROWSING A NEW MODEL FOR INFORMATION FILTERING BASED ON USER PROFILES AND DATA CLUSTERING

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
1353-2642
DOI
10.1108/eb024556
Publisher site
See Article on Publisher Site

Abstract

Hypertext users often experience the lost in hyperspace problem. This study suggests a solution which restricts the amount of information made available to the user, thus allowing improved hypertext browsing. An algorithm calculates the set of most relevant hypertext nodes for the user, utilising the user profile and data clustering technique. The result is an optimal cluster of relevant data items, customtailored for each user's needs.

Journal

Online and CD-Rom ReviewEmerald Publishing

Published: Jan 1, 1996

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