%0 Journal Article
%T An N-Gram Prediction Model Based on Web-Log Mining<br>基于Web-Log Mining的N元预测模型
%A SU Zhong
%A MA Shao-ping
%A YANG Qiang
%A ZHANG Hong-jiang
%A <br>苏中
%A 马少平
%A 杨强
%A 张宏江
%J 软件学报
%D 2002
%I 
%X As an increasing number of users access information on the Web, there is a great opportunity to learn about the users?probable actions in the future from the server logs. In this paper, an n-gram based model is presented to utilize path profiles of users from very large data sets to predict the users?future requests. Since this is a prediction system, the recall cannot be measured in a traditional sense. Therefore, the notion of applicability is presented to give a measure of the ability to predict the next document.The new model is based on a simple extension of existing point-based models for such predictions,but the results show that by sacrificing the applicability somewhat one can gin a great deal in prediction precision.The result can potentially be applied to awide range of applications on the Web,including pre-sending,pre-fetching,enhancement of recommendation systems as well as Web caching po;icies.The tests are based on three realistic Web logs.The new algorithm shows a marked improvement in precision and applicability over previous approaches.
%K Web mining
%K data mining
%K prediction<br>Web
%K mining
%K 数据挖掘
%K 预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=F49E49D34589DF34&yid=C3ACC247184A22C1&vid=FC0714F8D2EB605D&iid=CA4FD0336C81A37A&sid=58F693790F887B3B&eid=A8DE7703CC9E390F&journal_id=1000-9825&journal_name=软件学报&referenced_num=11&reference_num=5