基于Web日志的实时推荐系统  

Real-time Recommendation System Based on Web Log

作　　者：刘敏娴[1,2] 夏阳[2] 

机构地区：[1]徐州师范大学现代教育技术中心,徐州221116 [2]中国矿业大学计算机科学与技术学院,徐州221008

出　　处：《计算机工程》2009年第23期47-49,共3页Computer Engineering

基　　金：徐州师范大学校级基金资助项目(07XLB21)

摘　　要：针对个性化实时推荐系统的不足,提出通过构造BP树的方法压缩访问事务集。采用一个实时推荐的系统模型,将耗时的数据预处理放在离线模块,实时推荐采用动态修剪BP树的方法,穿过访问模式树的相关部分,利用网页推荐算法得到频繁访问集,生成推荐集。结果表明该算法只需扫描数据库一次,得到的频繁模式可满足页面实时推荐的快速需求。Aiming at the insufficiency of personalized real-time recommendation system, this paper proposes the theory through constructing the BP tree method, and compressing visit business collection, using a Real-Time Recommendation System（RTRS） model, putting time-consuming data pre-processing module on the off-line one, recommending the use of dynamic BP tree pruning method in real-time, passing through the visit of the relevant parts of the pattern tree, obtaining the frequent visit collection by way of the homepage recommendation algorithm so as to produce recommendation collection. Result indicates that this algorithm only needs to scan the database one time, the frequent pattern obtained can meet the rapid demands of the Web page recommendation in real-time.

关 键 词：数据挖掘 数据预处理 关联规则 实时推荐 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]