摘要
在网络使用挖掘 (web usage m ining)中 ,分析用户的行为模式是一个关键的问题 ,尤其对于匿名用户特征挖掘更有实际意义 ,首先介绍如何从网络使用数据 (web usage data)中提取出会话 (session)信息 ,接着讨论会话的特征抽取和特征空间 (feature space)的表述方式 ,并以此为基础提出了一种建立在会话特征信息上的匿名用户的网络浏览特征挖掘方法算法 ,这种算法在提高精确性的基础上减少了计算耗费 ,可以较好地解决路径的变长。
Analysing a user's behaviour pattern based on his interacting with a website is a key problem in web usage mining, especially to an anonymous user. First discussed in this paper is how to extract session information from web usage data, and then introduced is the session feature extracting and feature space description. Based on these, a highly efficient web browsing feature mining algorithm of an anonymous user is proposed. This algorithm reduces the computation consumption based on enhancing the accuracy. It may solve these questions well such as change path length, the directivity and dynamic clustering.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2002年第12期1758-1763,共6页
Journal of Computer Research and Development
基金
国家自然科学基金重点项目基金资助 (6993 3 0 10 )
