论文部分内容阅读
为了分析网络用户的浏览行为特征,实现科学平台的网络个性化服务,用广义频繁子序列挖掘算法,该算法挖掘Web服务器日志中的用户浏览路径,设计科学平台用户的浏览模式,为用户提供主动式信息服务。经过对日志文件的预处理,得到用户会话文件,然后采用广义频繁子序列挖掘算法对用户浏览模式进行识别。实际应用表明,这种广义频繁子序列识别方法能够有效地发现用户的兴趣所在,从而更好地为用户在线浏览提供帮助。
In order to analyze the browsing behavior characteristics of network users and realize the network personalized service of the scientific platform, a generalized frequent sub-sequence mining algorithm is used to mine the user browsing path in the web server log and design the browsing mode of the scientific platform users to provide users with initiative Information Service. After preprocessing the log files, the user session files are obtained, and then the generalized frequent sub-sequence mining algorithm is used to identify the user browsing modes. The practical application shows that this method of identifying generalized frequent sub-sequences can effectively find the user’s interest and help users to browse online better.