A self-organizing semantic map for information retrieval
SIGIR '91 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval
Helping the user to select a link
Hypermedia
Automatic structuring and retrieval of large text files
Communications of the ACM
Automatic hypertext link typing
Proceedings of the the seventh ACM conference on Hypertext
Self-Organizing Maps
Adaptive HyperText and Hypermedia
Adaptive HyperText and Hypermedia
Ending the Tyranny of the Button
IEEE MultiMedia
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A prototype of an open and adaptive hypertext learning environment on the Web is presented. The nodes of the hypertext system are sorted in clusters which are ordered on a map by a self organizing neural network. This map represents the Information Domain Model on which an overlay model of the learning goal and of the user knowledge is built up. The User Model is made up of a user knowledge model and a preference model that takes into account the user's attitude to approaching the information necessary to achieve the learning goal. The Information Domain Model allows users to add new documents to the system that are ordered by the neural network in the appropriate clusters. This maintains the consistency of the User Model and of the learning goal when the number of documents grows.