网络教育要想为学习者提供个性化的指导和服务,必须注重教学过程跟踪,注意对学生学习行为的分析.Web服务器日志中记录了访问者的所有信息,通过数据挖掘的方法可以获得需要的有用知识,并由此得到用户的访问模式.文中使用Web日志挖掘的方法分析学生的网上学习行为,通过数据过滤、用户辨别和会话辨别,采用模糊集和粗糙集的方法获得访问用户的聚类和分类等有用信息.实验证明,通过Web日志挖掘的方法,可以更好地了解学生的学习偏好,提高教学服务质量.%In order to provide personalized guidance and service for learners, online education must focus on tracking the process of teaching, pay attention to analyze the student's learning behavior. Web server logs keep visitor's all information, so useful knowledge needed can be gotten by data mining , and thus the user's access patterns. It uses analysis of Web log mining methods of online learning behavior of students, through data filtering, user identification and session identification,use fuzzy set and rough set way to get access to the user useful information such as clustering and classification. Experiments show that,can better understand the learning preferences, can improve the teaching quality of service through Web log mining.
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