一种提高过滤用户偏好精度的数据采集方法

A Method of Data Collecting to Improve the Precision of Filtering User Preference

采用数据挖掘技术中的关联分析和聚类方法,重点研究Web日志兴趣发现的理论和方法,指出普通日志记录方法的局限性,提出过滤用户偏好的定制Web日志方法,实验结果验证通过该方法采集的数据,可以发现隐藏在日志数据中的关联规则,同时找到相似用户的兴趣和偏好,并且能够提高过滤用户兴趣偏好的精度。

Using the methods of association analysis and clustering in the field of data mining, the paper focuses on the theories and methods of discovering user interests and points out the limitations of standard Web log. So it proposes a method of customized Web log in order to enhance the precision of user interests and preferences. The outcome of experiment shows that, by the method, Web log data hidden in the association rules as well as interests and preferences of similar users can be found, the precision of filtering user interest can be improved at the same time.