Abstract
A Web recommender system based on the inference from a user’s Web-browsing behavior has been proposed and implemented. This system is capable of recommending items of interest to a user and specific Web-browsing action on the current item using a novel similarity measure approach. The recommender is adaptive to individual user’s preference as well as a user’s changing interest via a dynamic user feedback mechanism and empirical statistics on Web-browsing actions taken. Furthermore, users’ quantitative comments and the qualitative measures of users’ behavior provide an ideal setting to ascertain the premise, implicitly used in several other existing recommender systems, that there is a correlation between preference information and browsing behavior.
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References
Chirita, P.-A., Firan, C.S., Nejdl, W.: Personalized Query Expansion for the Web. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 7–14 (2007)
Dumais, S., Cutrell, E., Cadiz, J.J., Jancke, G., Sarin, R., Robbins, D.C.: Stuff I’ve Seen: A System for Personal Information Retrieval and Re-Use. In: Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 72–79 (2003)
Marcialis, I., Vita, E.D.: SEARCHY: An Agent to Personalize Search Results. In: Proceedings of the 3rd International Conference on Internet and Web Applications and Services (ICIW 2008), pp. 512–517 (2008)
Morita, T., Hidaka, T., Tanaka, A., Kato, Y.: System for Reminding a User of Information Obtained Through a Web Browsing Experience. In: Proceedings of the 16th International World Wide Web Conference, WWW 2007, pp. 1327–1328 (2007)
Takano, K., Li, K.F.: An Adaptive Personalized Recommender Based on Web-Browsing Behaviour Learning. In: Proceedings of the 2009 IEEE International Symposium on Mining and Web (MAW 2009), pp. 654–660 (2009)
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Takano, K., Li, K.F. (2010). Adaptive Recommendation for Preferred Information and Browsing Action Based on Web-Browsing Behavior. In: Kitagawa, H., Ishikawa, Y., Li, Q., Watanabe, C. (eds) Database Systems for Advanced Applications. DASFAA 2010. Lecture Notes in Computer Science, vol 5982. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12098-5_52
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DOI: https://doi.org/10.1007/978-3-642-12098-5_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12097-8
Online ISBN: 978-3-642-12098-5
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