Computer Engineering and Applications ›› 2008, Vol. 44 ›› Issue (28): 91-94.DOI: 10.3778/j.issn.1002-8331.2008.28.032

• 网络、通信、安全 • Previous Articles     Next Articles

Personalized E-Commerce real-time recommendation based on information flow

SHEN Ai-guo   

  1. Jiangsu Nantong No.3 Construction Group Co. LTD,Nantong,Jiangsu 226100,China
  • Received:2008-01-07 Revised:2008-04-08 Online:2008-10-01 Published:2008-10-01
  • Contact: SHEN Ai-guo

基于信息流的实时电子商务推荐策略

沈爱国   

  1. 江苏南通三建集团有限公司,江苏 南通 226100
  • 通讯作者: 沈爱国

Abstract: In dealing with the needs of real-time personalized recommendation,personalized recommendation method for E-Commerce system is studied through deep mining of customer’s browse record based on information flow representation,generation and analysis.In order to manage information flow,this paper proposes a personalized recommendation algorithm,which consists of four phases:information flow definition,information flow evaluation,knowledge matching and website dynamic organization.A model including client,server and storage system is designed based on J2EE.To demonstrate the practical usefulness of this methodology,a real-life case is illustrated,which shows recommendation accuracy increases according to the increase of training number,and superior to association rule.

Key words: personalized recommendation, information flow, algorithm design

摘要: 针对企业对实时个性化推荐的需求,基于信息流的表达、生成和分析对顾客访问记录进行了深层次挖掘,研究了电子商务系统实时个性化推荐策略。提出了包含信息流定义、信息流评价、知识匹配、网站动态组织等算法在内的个性化推荐算法。基于J2EE技术完成了包含客户端、服务器端和存储系统在内的实时动态个性化推荐系统的结构设计。实例表明,随着训练次数的增加推荐准确度呈升高的趋势,并优于关联规则法。

关键词: 个性化推荐, 信息流, 算法设计