Abstract
Some challenges for Website designers are to provide correct and useful information to individual users with different backgrounds and interests, as well as to increase user satisfaction. Intelligent Web agents offer a potential solution to meet such challenges. A Web agent collects information, discovers knowledge through Web mining and users’ behavior analysis, and applies the discovered knowledge to give dynamically recommendations to Website users, to update Web pages, and to provide suggestions to Website designers. The basic functionalities and components of an intelligent Web agent are discussed. A prototype system, called PagePrompter, is described. The knowledge of the system is extracted based on a combination of Web usage mining and machine learning.
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Yao, Y.Y., Hamilton, H.J., Wang, X. (2002). PagePrompter: An Intelligent Web Agent Created Using Data Mining Techniques. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds) Rough Sets and Current Trends in Computing. RSCTC 2002. Lecture Notes in Computer Science(), vol 2475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45813-1_67
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DOI: https://doi.org/10.1007/3-540-45813-1_67
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