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A Recommendation Method in E-Commerce Based on Product Taxonomy Graph

In: 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings

Author

Listed:
  • Qian Liu

    (Harbin Institute of Technology)

  • Hongzhi Wang

    (Harbin Institute of Technology)

  • Hong Gao

    (Harbin Institute of Technology)

  • Qi Lv

    (Harbin Institute of Technology)

  • Jianyu Fu

    (Harbin Institute of Technology)

Abstract

The data of e-commerce is growing at a rapid speed. As a result, customers are no longer able to achieve what they want to buy in a relatively short time. Collaborative Filtering (CF) is the most acceptable method about recommendation. However it has two limitations. One is sparsity, the other is scalability. In this paper we give a methodology to solve the problems based on product taxonomy graph. Data mining on product taxonomy graph helps make the transaction data in more aggregated way which is expected to solve the sparsity and scalability problem in CF.

Suggested Citation

  • Qian Liu & Hongzhi Wang & Hong Gao & Qi Lv & Jianyu Fu, 2013. "A Recommendation Method in E-Commerce Based on Product Taxonomy Graph," Springer Books, in: Bing Xu (ed.), 2012 International Conference on Information Technology and Management Science(ICITMS 2012) Proceedings, edition 127, pages 411-422, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-34910-2_47
    DOI: 10.1007/978-3-642-34910-2_47
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