Abstract
We propose an algorithm for learning hierarchical user interest models according to the Web pages users have browsed. In this algorithm, the interests of a user are represented into a tree which is called a user interest tree, the content and the structure of which can change simultaneously to adapt to the changes in a user's interests. This expression represents a user's specific and general interests as a continuum. In some sense, specific interests correspond to short-term interests, while general interests correspond to long-term interests. So this representation more really reflects the users' interests. The algorithm can automatically model a user's multiple interest domains, dynamically generate the interest models and prune a user interest tree when the number of the nodes in it exceeds given value. Finally, we show the experiment results in a Chinese Web Site.
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Foundation item: Supported by the National Natural Science Fundatio of China (69973012, 60273080)
Biography: YANG Feng-qin(1978-), female, Ph. D. candidate, research direction: Web mining, intelligent user interface, constraint programming.
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Feng-qin, Y., Tie-li, S. & Ji-gui, S. Learning hierarchical user interest models from Web pages. Wuhan Univ. J. Nat. Sci. 11, 6–10 (2006). https://doi.org/10.1007/BF02831694
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DOI: https://doi.org/10.1007/BF02831694