摘要
如何精准地捕获读者的需求并分析客户的需求是设计个性化推荐系统的关键性问题。本文借鉴大型电子商务网站的个性化推荐技术,采用WEB挖掘的方式,采集海量的读者数据,运用CPM算法对读者及资源进行关联,根据读者的查询记录、借阅历史等信息实现智能推荐相关的书目,以满足读者个性化的服务需求。
It＇s essential for an individualized recommendation system to precisely know and analyze readers＇ requirements. This paper draws on the experience of individualized recommendation technology of large-scale Ecommerce websites, adopts WEB data mining, collects massive reader data, associates readers with resources with CMP algorithm, and realizes intelligent recommendation of related books to readers on the basis of inquiry records, borrowing history and other information, which can meet the requirements of individualized service.
出处
《安徽电子信息职业技术学院学报》
2014年第3期24-28,共5页
Journal of Anhui Vocational College of Electronics & Information Technology
关键词
WEB挖掘
数据处理
算法
WEB data mining
data processing
algorithm
