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Title:
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SEQUENCE PREDICTION FOR ADAPTIVE NAVIGATION SUPPORT |
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Author(s):
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Pascal Dayre , Hadj Batatia |
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ISBN:
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972-8939-03-5 |
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Editors:
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Pedro Isaías, Piet Kommers and Maggie McPherson |
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Year:
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2005 |
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Edition:
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Single |
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Keywords:
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Adaptive Navigation, Document Mining, Machine Learning. |
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Type:
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Short Paper |
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First Page:
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610 |
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Last Page:
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614 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Hypermedia has a non-linear structure of informations creating an information space with redondant paths. Although several paths offer greater flexibility, the user can be disoriented. It is the well-know lost in hyperspace syndrome. Adaptive navigation systems has been proposed as means to aid users in finding their way through information spaces. The contribution of this paper is to propose a solution using the user navigation sequence prediction and his cognitive process. Our adaptive navigation support combines adaptive link and link generation. Short cuts are generated dynamically in order to accelerate the user navigation to the most relevant information pieces using an information contribution function. This solution can be usable on any content without overload on the authoring process comparing to the semantic web that need explicit relationship between content parts. |
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