E-COMMERCE RECOMMENDATION SYSTEM BASED OX ON-LINE DEMAND HINTS

摘要：

Due to offline clients demand analysis and processing, traditional recommendation systems lose the temporality- and the real-time. In order to deal with them, a novel recommendation system was proposed based on on-line demand estimation. And its basic models, data structures, algorithms and working flows were described as following. Then it utilized clients1 demand hints to analyze and to predict shopping tendency. Furthermore, a product-demand overlay space was presented to match and recommend communities. On-line shopping simulation results show that the novel has better real-time and degree of satisfaction than the traditional does.

关键词： E-commerce Recommendation system On-line Demand hint

作者: Long-jiang Tan

作者单位: College of information,Southwestern University of Finance and Economics,Chengdu 610074,China College of Economics & Finance,HuaQiao University,Quanzhou 362021,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 469-472

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）