Abstract
The growth of the Internet has resulted in an increasing need for personalized information systems. The paper describes an autonomous agent, WebBot: Web Robot Agent, which integrates with the web and acts as a personal recommender system that cooperates with the user on identifying interesting pages. Hybrid components from collaborative filtering and content-based filtering, a hybrid recommender system can overcome traditional shortcomings. In this paper, we present an effective hybrid collaborative filtering and content-based filtering for improved recommender system. Experimental results indicate the hybrid collaborative filtering and content-based filtering better than collaborative, content-based, and combined filtering approach.
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© 2004 Springer-Verlag Berlin Heidelberg
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Jung, KY., Park, DH., Lee, JH. (2004). Hybrid Collaborative Filtering and Content-Based Filtering for Improved Recommender System. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds) Computational Science - ICCS 2004. ICCS 2004. Lecture Notes in Computer Science, vol 3036. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24685-5_37
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DOI: https://doi.org/10.1007/978-3-540-24685-5_37
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