Abstract
By using ART neural network and data mining technology, this study builds a typical online recommendation system. It can automatically cluster population characteristics and dig out the associated characteristics. Aiming at the characteristics of recommendation system and users’ attribute weights, this paper propose a modified ART algorithm for clustering MART algorithm. It makes recommendation system to set the weight value of each attribute node based on the importance of user attributes. The experiment shows that the MART algorithm has better performance than the conventional ART algorithm and can get more reasonable and flexible clustering results.
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© 2011 Springer-Verlag Berlin Heidelberg
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Chen, Q., Chen, Q., Wang, K., Tang, Z., Pei, Y. (2011). Research on Automatic Recommender System Based on Data Mining. In: Zhiguo, G., Luo, X., Chen, J., Wang, F.L., Lei, J. (eds) Emerging Research in Web Information Systems and Mining. WISM 2011. Communications in Computer and Information Science, vol 238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24273-1_4
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DOI: https://doi.org/10.1007/978-3-642-24273-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24272-4
Online ISBN: 978-3-642-24273-1
eBook Packages: Computer ScienceComputer Science (R0)