Application of Improved Collaborative Filtering in the Recommendation of E-commerce Commodities
作者: Dan ChangHao Yu GuiRui FanZe Zhou FanJi Tian
刊名: International Journal of Computers Communications & Control, 2019, Vol.14 (4), pp.489-502
来源数据库: Agora University
DOI: 10.15837/ijccc.2019.4.3594
关键词: Recommendation precisionRecommendation efficiencySupport vector machine (SVM)Collaborative filtering
原始语种摘要: Problems such as low recommendation precision and efficiency often exist in traditional collaborative filtering because of the huge basic data volume. In order to solve these problems, we proposed a new algorithm which combines collaborative filtering and support vector machine (SVM). Different with traditional collaborative filtering, we used SVM to classify commodities into positive and negative feedbacks. Then we selected the commodities that have positive feedback to calculate the comprehensive grades of marks and comments. After that, we build SVM-based collaborative filtering algorithm. Experiments on Taobao data (a Chinese online shopping website owned by Alibaba) showed that the algorithm has good recommendation precision and recommendation efficiency, thus having certain...
全文获取路径: PDF下载  阿戈拉大学 

  • commerce 商务
  • filtering 滤波
  • precision 精度
  • SVM 共享虚拟存储器
  • machine 机器
  • recommendation 建议
  • algorithm 算法
  • classify 分类
  • vector 矢量
  • marks 货物包装标记