摘要
点击流数据是分析互联网用户心理倾向的关键,用户感兴趣的页组关联就隐藏于WEB日志之中.网站页面间的隐式关联可以通过分析点击流数据实现.给出了一种挖掘关联页面的方法.关联页面发现算法采用了一种类似于Apriori的模型.算法克服了前人关联页面算法的一些缺点,能够更好地适应复杂的互联网环境.
The Clickstream data is the key to the analysis of Internet users psychological tendency, and the association of the user interesting pages group is hidden in the WEB log. Implied association between Web pages can be achieved by analyzing the click stream data. This paper puts forward a method of mining association page. Associated page searching algorithm adopted a model similarly to the Apriori. This algorithm overcomes some shortcomings of predecessors’ association page algorithm can better adapt to the complex Internet environment.
出处
《计算机系统应用》
2014年第9期167-169,共3页
Computer Systems & Applications