计算机工程 ›› 2012, Vol. 38 ›› Issue (20): 172-175.doi: 10.3969/j.issn.1000-3428.2012.20.044

• 人工智能及识别技术 • 上一篇    下一篇

基于时间加权的综合电子商务物品关联推荐

卫 望,张晓烨,刘 悦   

  1. (上海大学计算机工程与科学学院,上海 200072)
  • 收稿日期:2011-11-29 修回日期:2012-02-02 出版日期:2012-10-20 发布日期:2012-10-17
  • 作者简介:卫 望(1983-),男,硕士研究生,主研方向:机器学习,数据挖掘;张晓烨,工程师;刘 悦,副教授、博士
  • 基金项目:

    上海市自然科学基金资助项目(09ZR1412600);上海大学研究生创新基金资助项目(SHUCX112162);上海市重点学科建设基金资助项目(J50103)

Item Association Recommendation for Comprehensive E-commerce Based on Time Weighting

WEI Wang, ZHANG Xiao-ye, LIU Yue   

  1. (School of Computer Engineering and Science, Shanghai University, Shanghai 200072, China)
  • Received:2011-11-29 Revised:2012-02-02 Online:2012-10-20 Published:2012-10-17

摘要: 提出一种基于时间加权的综合电子商务物品关联推荐项生成和排序方法。通过垂直和水平2种数据格式以及字典散列技术,快速得到物品的候选推荐项。采用时间加权计算方法修正Jaccard相似度系数,结合关联度得到候选推荐项的排序,从而保证推荐的多样性,并兼顾用户的消费喜好。应用结果表明,该方法能提高推荐项的生成效率,具有较好的在线推荐效果。

关键词: 关联推荐, 时间加权, 综合电子商务, 字典散列, 关联度

Abstract: This paper proposes an association recommend item generating and sorting method for comprehensive e-commerce based on time weighting. Mixture of vertical, horizontal data formats and hash technology are employed to obtain the recommended candidates efficiently. Improved Jaccard similarity coefficient with time factor is taken into calculation, meanwhile it combines with the degree of association for the candidates sorting to balances the diversity of recommendation and consumers’ preference. Application results show that this method has better performance in recommend-items generating efficiency and online recommending effect.

Key words: association recommendation, time weighting, comprehensive e-commerce, dictionary hash, degree of association

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