基于关联规则的Web日志挖掘算法研究
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摘要
关联规则挖掘是数据挖掘研究领域中的一个重要的方法,旨在挖掘事务数据库中有趣的模式。阐述了Web日志挖掘和关联规则的基本内容,分析了经典Apriori算法的不足之处,提出了改进的算法。另外,利用论坛Web日志数据进行了对比实验,实验结果表明改进后的算法性能有较大提高。将改进后的算法应用于网络论坛的日志挖掘,找出用户的个性化访问模式,从而提高论坛的服务质量。
Association rule mining is an important method in the field of data mining research;its purpose is to mine interesting associations in transaction database.The basic content of Web Log Mining and Association rule is described in this paper.And the shortcomings of classical Apriori algorithm are analyzed,an improved algorithm is proposed.Besides compariso the comparative experiments are conducted utilizing the BBS web log data.The results demonstrate that the improved algorithm is better in efficiency.The improved algorithm is applied to the web log mining of BBS to find the personalized visiting mode,in this way the service quality of BBS is enhanced.
引文
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