基于访问日志挖掘的高校综合信息门户页面推荐研究
    点此下载全文
引用本文:杨富华,彭钢.基于访问日志挖掘的高校综合信息门户页面推荐研究[J].计算技术与自动化,2016,(4):102-106
摘要点击次数: 755
全文下载次数: 0
作者单位
杨富华,彭钢 (西南医科大学 现代教育技术中心四川 泸州646000) 
中文摘要:研究基于访问日志挖掘的高校综合信息门户页面推荐。从高校综合信息门户服务器日志中获取用户日志数据,对日志数据中的“脏”数据进行预处理,通过改进的K-means聚类算法将用户浏览兴趣度数据集划分为多个具有相近兴趣度的用户集合,凭此为用户提供个性化的页面推荐。实验结果表明,在高校综合信息门户页面推荐方面具有不错的效果。
中文关键词:用户日志挖掘  高校综合信息门户  页面推荐
 
Page Recommendation of College Synthetical Information Portals Based on Server Logs Mining
Abstract:This paper discussed a page recommendation of college synthetical information portals based on server logs mining. Firstly, the user log data was obtained from server logs, which were then pretreated with “dirty” data. Secondly, the interest-measure of each user pairs was calculated by the processed data sets, and the data set of interest-measure of each user pairs was divided into multiple classes with similar interest-measure based on improved K-means clustering algorithm. Finally, personalized page recommendation method was provided to each user. The experimental results prove the effectiveness of the method in college information portals.
keywords:server logs mining  college synthetical information portals  page recommendation
查看全文   查看/发表评论   下载pdf阅读器