文件名称:PersonalizedRecommendationsEbusiness
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简要介绍了电子商务推荐系统的概念、作用及组成构件,给出了推荐技术分类标准,系统综述了协同
过滤推荐、基于内容推荐、基于人口统计信息推荐、基于效用推荐、基于知识推荐和基于规则推荐等6 种主要的推
荐技术。对这些推荐技术的优缺点进行了比较,介绍了推荐评价技术。重点评述了电子商务个性化推荐领域中的
研究热点问题,并分析了目前国内电子商务个性化推荐理论研究和应用现状,最后提出了电子商务个性化推荐领
域所面临的挑战。-To make E- business system actively recommend product s to users according to their interest s , re2
search on E- business recommended systems was firstly described. Concept s , functions and constituent s of E-
business recommended system were briefly int roduced. The technical recommendation standard was given. Six
main recommend technologies such as collaborative filtering recommendation , recommendation based on con2
tent s , population statistics , efficiency , information and rules were mentioned. Advantages and disadvantages of
these above- mentioned technical recommendations were provided. Recommendation evaluation was also int ro2
duced. Hot topics in personalized E- business recommendation research were emphasized. Then , existing prob2
lems on personalized recommendation in China were analyzed. Future research challenges facing E- business
personalized recommendation were presented at last.
过滤推荐、基于内容推荐、基于人口统计信息推荐、基于效用推荐、基于知识推荐和基于规则推荐等6 种主要的推
荐技术。对这些推荐技术的优缺点进行了比较,介绍了推荐评价技术。重点评述了电子商务个性化推荐领域中的
研究热点问题,并分析了目前国内电子商务个性化推荐理论研究和应用现状,最后提出了电子商务个性化推荐领
域所面临的挑战。-To make E- business system actively recommend product s to users according to their interest s , re2
search on E- business recommended systems was firstly described. Concept s , functions and constituent s of E-
business recommended system were briefly int roduced. The technical recommendation standard was given. Six
main recommend technologies such as collaborative filtering recommendation , recommendation based on con2
tent s , population statistics , efficiency , information and rules were mentioned. Advantages and disadvantages of
these above- mentioned technical recommendations were provided. Recommendation evaluation was also int ro2
duced. Hot topics in personalized E- business recommendation research were emphasized. Then , existing prob2
lems on personalized recommendation in China were analyzed. Future research challenges facing E- business
personalized recommendation were presented at last.
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电子商务个性化推荐研究.pdf
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