A User-Centered Approach to Adaptive Hypertext Based on an Information Relevance Model

摘要: Rapid and effective to information in large electronic documentation systems can be facilitated if relevant an individual user's content automatically supplied this user. However most of knowledge on contextual relevance is not found within the contents documents, it rather established incrementally by users during access. We propose a new model for interactively learning retrieval, adapting retrieved user profiles. The model, called network, records references based feedback specific queries It also generalizes such later derive similar network lets filter context relevance. Compared other approaches, does require any prior nor training. More importantly, our approach adaptivity user-centered. facilitates acceptance understanding giving them shared control over adaptation without disturbing their primary task. Users easily when adapt use adapted system. Lastly, independent particular application used access information, supports sharing adaptations among users.