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A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance ModelRapid and effective to information in large electronic documentation systems can be facilitated if information relevant in an individual user's content can be automatically supplied to this user. However most of this knowledge on contextual relevance is not found within the contents of documents, it is rather established incrementally by users during information access. We propose a new model for interactively learning contextual relevance during information retrieval, and incrementally adapting retrieved information to individual user profiles. The model, called a relevance network, records the relevance of references based on user feedback for specific queries and user profiles. It also generalizes such knowledge to later derive relevant references for similar queries and profiles. The relevance network lets users filter information by context of relevance. Compared to other approaches, it does not require any prior knowledge nor training. More importantly, our approach to adaptivity is user-centered. It facilitates acceptance and understanding by users by giving them shared control over the adaptation without disturbing their primary task. Users easily control when to adapt and when to use the adapted system. Lastly, the model is independent of the particular application used to access information, and supports sharing of adaptations among users.
Document ID
19990111709
Acquisition Source
Ames Research Center
Document Type
Reprint (Version printed in journal)
Authors
Mathe, Nathalie
(NASA Ames Research Center Moffett Field, CA United States)
Chen, James
(RECOM Technologies, Inc. Moffett Field, CA United States)
Date Acquired
August 19, 2013
Publication Date
October 1, 1994
Subject Category
Computer Programming And Software
Report/Patent Number
FIA-94-13
Meeting Information
Meeting: User Modeling
Location: Hyannis, MA
Country: United States
Start Date: August 15, 1994
End Date: August 19, 1994
Distribution Limits
Public
Copyright
Other

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