Web systems suffer from an inability to satisfy heterogeneous needs of many users. For example, Web courses present the same static learning material to students with widely differing knowledge of the subject. Web e-stores offer the same selection of featured items to customers with different needs and preferences. Virtual museums on the Web offer the same guided tour to visitors with very different goals and interests. Health information sites present the same information to readers with different health problems. A remedy for the negative effects of the traditional "one-size-fits-all" approach is to develop systems with an ability to adapt their behavior to the goals, tasks, interests and other features of individual users and groups of users. The adaptive web is a relatively young research area. Starting with a few pioneering works on adaptive hypertext in early 1990, it now attracts many researchers from different communities such as hypertext, user modeling, machine learning, natural language generation, information retrieval, intelligent tutoring systems, cognitive science and Web-based education.
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André et al. (2002) studied this question.
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