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文章基本信息

  • 标题:A Commodity Information Search Model of E-Commerce Search Engine Based on Semantic Similarity and Multi-Attribute Decision Method
  • 本地全文:下载
  • 作者:Ziming Zeng
  • 期刊名称:International Journal of Business and Management
  • 印刷版ISSN:1833-3850
  • 电子版ISSN:1833-8119
  • 出版年度:2010
  • 卷号:5
  • 期号:7
  • 页码:136
  • DOI:10.5539/ijbm.v5n7p136
  • 出版社:Canadian Center of Science and Education
  • 摘要:The paper presented an intelligent commodity information search model, which integrates semantic retrieval and
    multi-attribute decision method. First, semantic similarity is computed by constructing semantic vector-space, in
    order to realize the semantic consistency between retrieved result and customer’s query. Besides, TOPSIS
    method is also utilized to construct the comparison mechanism of commodity by calculating the utility value of
    each retrieved commodity. Finally, the experiment is conducted in terms of accuracy and customer acceptance
    rate, and the results verify the effectiveness of the model and it can improve the precision of the commodity
    information search.
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