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Research on Automatic Recommender System Based on Data Mining

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Emerging Research in Web Information Systems and Mining (WISM 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 238))

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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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Author information

Authors and Affiliations

  1. Department of computer science and technology, Zhejiang University of technology, HangZhou, 310000, China

    Qingzhang Chen, Qiaoyan Chen, Kai Wang, Zhongzhe Tang & Yujie Pei

Authors
  1. Qingzhang Chen
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  2. Qiaoyan Chen
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  3. Kai Wang
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  4. Zhongzhe Tang
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  5. Yujie Pei
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Editor information

Editors and Affiliations

  1. Department of Computer and Information Science, University of Macau, Taipa, Macau, China

    Gong Zhiguo

  2. School of Computer, Shanghai University, 200444, Shanghai, China

    Xiangfeng Luo

  3. School of Computer and Software, Taiyuan University of Technology, 030024, Taiyuan, China

    Junjie Chen

  4. Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan, Hong Kong SAR, China

    Fu Lee Wang

  5. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

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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)

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