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Application of Vague Set in Recommender Systems

In: Liss 2012

Author

Listed:
  • Cui Chunsheng

    (Henan University of Economics and Law)

  • Zang Zhenchun

    (Henan University of Economics and Law)

  • Liu Feng

    (Central Institute for Correctional Police)

  • Qu Ying

    (HeiBei University of Science and Technology)

Abstract

In the paper, vague set theory is introduced into the study of recommender systems to solve its core problem which is similarity. The existence of uncertainty of customer behavior in the course of e-commerce provides a theoretical basis for the introduction of Vague set. Recommendation of goods relies on the degree of similarity between customers or goods, while the calculation of similarity is a mature area in the research of Vague set. First, Different customer types are identified according to the general shopping way in e-commerce. Then based on the customer classification, statistical methods are used to define the Vague value of the commodity. This method makes a perfect combination e-commerce recommendation system and Vague set and provides new idea for the study of e-commerce recommendation system.

Suggested Citation

  • Cui Chunsheng & Zang Zhenchun & Liu Feng & Qu Ying, 2013. "Application of Vague Set in Recommender Systems," Springer Books, in: Zhenji Zhang & Runtong Zhang & Juliang Zhang (ed.), Liss 2012, edition 127, pages 1353-1359, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-32054-5_192
    DOI: 10.1007/978-3-642-32054-5_192
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