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Titlebook: Adaptive Hypertext and Hypermedia; Peter Brusilovsky,Alfred Kobsa,Julita Vassileva Book 1998 Springer Science+Business Media Dordrecht 199

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https://doi.org/10.1007/978-3-476-03897-5oices. An adaptive hypertext system can overcome these disadvantages by recommending information to users based on their specific information needs and preferences. Simple associative matrices provide an effective way of capturing these user preferences. Because the matrices are easily updated, they
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https://doi.org/10.1007/978-3-476-04097-8avor of non-linear hypertext writing. In this paper, we investigate how hypertext — in its current node-and-link form — can be augmented by an adaptive, user-model-driven tool. Currently the reader of a document has to adapt to that document — if the detail level is wrong the reader either skims the
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https://doi.org/10.1007/978-3-476-04097-8y level. We introduce ITSs in general, discussing some of the psychological and pedagogical issues involved in using computers in education, and ANATOM-TUTOR in parlicular, and locate ANATOM-TUTOR’s user modelling component in the field of existing user models. Details of the user model’s constructi
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Alexander Olsen,Pamela Rossi Ciampolinit to the perceived needs of the user. Unless carefully designed, these changes may lead to an unpredictable, obscure and uncontrollable interface. Therefore the design of adaptive interfaces must ensure that users can inspect the adaptivity mechanisms, and control their results. One way to do this i
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Alexander Olsen,Pamela Rossi Ciampolinithe system knowledge about the user in order to allow informed decisions on how to adapt to match the user’s needs. Most of the research in this field, however, has been theoretical, “top-down.” Our approach, in contrast, was driven by the needs of the application and shows features of bottom-up, us
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