Abstract
As people’s web usage is growing bigger, personalized support for web browsing is in great demand. Furthermore, the diversity of a user’s interests demands an appropriate methodology for profiling multiple domains of user interests. To comply with such demands, we propose one feasible design approach to support personalized web usage, in which a web user agent takes over the task of learning and profiling the multiplicity and the changeability of user interests. To evaluate the advantages of this approach, we have constructed a personalized web supporting system, in which an autonomous agent, namely the web guide agent, utilizes the information gathered by the web user agent for adaptation, e.g., selective retrieval and re-ranking of web links, and automatic delivery of specific web pages. Compared to other design alternatives, the proposed scheme is operationally simple, while producing acceptably reliable outcome.
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Kook, H.J. (2005). Profiling Multiple Domains of User Interests and Using Them for Personalized Web Support. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538356_53
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DOI: https://doi.org/10.1007/11538356_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28227-3
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