Abstract
We present a framework of recommendation system by organize users into different data groups and performing collaborative filtering on each groups to overcome problems that traditional recommendation systems have. Extensive experiment shows that recommendation system can observe user’s behavioral characteristics better than previous approaches and can provide more accurate recommendation.
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Yoo, JH., Ahn, KS., Jun, J., Rhee, PK. (2004). A Recommendation System for Intelligent User Interface: Collaborative Filtering Approach. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30134-9_115
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DOI: https://doi.org/10.1007/978-3-540-30134-9_115
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