On Creating Adaptive Web Servers Using Weblog Mining
On Creating Adaptive Web Servers Using Weblog Mining
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发表时间：
2000-11
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通讯作者：
Tapan Kamdar;A. Joshi
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作者：
Tapan Kamdar;A. Joshi
从网站返回的内容的个性化通常是一个重要的问题，并且特别影响电子商务和电子服务。针对最终用户的适当信息或产品可以显著改变（更好地）用户在网站上的体验。Web个性化的一种可能方法是从存储在访问日志中的大量历史数据中挖掘典型的用户配置文件。在没有任何先验知识的情况下，无监督分类或聚类方法非常适合通过检查用户会话来分析用户访问的半结构化日志数据。用户访问配置文件是通过使用一个强大的模糊聚类算法的基础上，成对的相异聚类用户会话生成的。我们提出了一个系统，挖掘日志，以获得配置文件，并使用它们来自动生成一个网页，其中包含用户可能感兴趣的URL。我们还评估使用和不使用cookie的信息会话化的功效。
Personalization of content returned from a web site is an important problem in general, and affects e-commerce and e-services in particular. Targeting appropriate information or products to the end user can significantly change (for the better) the users experience on a web site. One possible approach to web personalization is to mine typical user profiles from the vast amount of historical data stored in access logs. In the absence of any a priori knowledge, unsupervised classification or clustering methods are ideally suited to analyze the semi-structured log data of user accesses by examining user sessions. User access profiles are generated by clustering user sessions on the basis of pair-wise dissimilarities using a robust fuzzy clustering algorithm.We present a system that mines the logs to get profiles and uses them to automatically generate a web page containing URLs the user might be interested in. We also evaluate the efficacy of sessionizing the information with and without the use of cookies.