期刊文献+

基于Web日志和缓存数据挖掘的个性化推荐系统 被引量:14

Personalization Recommendation System Based on Web Log & Cache Data Mining
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摘要 针对当前推荐系统中存在的问题,提出一个基于Web日志和缓存数据挖掘的个性化推荐系统.系统依据Web日志挖掘用户兴趣页面时综合考虑了访问次数、浏览时间和页面长度.通过对Web日志和缓存数据挖掘得到的兴趣页面的有效分类,构造不同用户的兴趣模型.系统能依据用户兴趣模型实现内容过滤推荐,同时也能通过比较不同用户的兴趣模型实现协作过滤推荐.经模拟实验测试表明,本文提出的推荐方法是可行并且有效的.
出处 《情报学报》 CSSCI 北大核心 2005年第3期324-328,共5页 Journal of the China Society for Scientific and Technical Information
基金 浙江省自然科学基金,浙江省科技厅资助项目
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参考文献11

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