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Web数据挖掘在个性化推荐服务的应用 被引量:6

Web data mining used in the personalized recommendation service
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摘要 随着Internet的迅速发展和普及,人们在网络上开展的活动也越来越多,尤其是电子商务的兴起,使得网上购物逐渐成为一种时尚。然而由于互联网上的信息量日益增长,人们面对这些庞大的信息感到无所适从,花费大量时间在搜寻信息上,因此如何为用户提供更好的服务变得非常迫切。本文以数据挖掘理论为基础,分析和探讨了关联规则挖掘算法并应用该方法实现web个性化推荐服务。 With the rapid development and popularization of the Internet, network activities are more and more frequent. Especially the booming Ecommerce makes online shopping new fashion. However, people are lost in the overwhelming information and spend lots of time on searching, because of the progressively increasing of the amount of information on the Internet. Therefore, it is very necessary to provide better service for users. Here we analyzed and discussed association rule mining algorithms and used this to achieve web personalized recommendation service, based on the data mining theory.
出处 《微计算机信息》 2009年第12期195-196,189,共3页 Control & Automation
关键词 使用挖掘 关联规则 APRIORI 个性化推荐 Web usage mining association rule Apriori personalized recommendation
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