期刊文献+

基于Apriori算法的Web日志文件挖掘模块的实现

Implementation on Web Log File Mining Model Based on Apriori Algorithm
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摘要 为了识别用户浏览模式,实现利用关联规则挖掘算法Apriori对Web应用挖掘过程中预处理阶段所产生的用户会话文件进行挖掘的模块,该模块针对用户选定的若干页面产生满足最小支持度和最小置信度的页面之间的强关联规则。关联规则挖掘结果对网站管理员重新调整网站结构、通过预测用户浏览模式提供推送服务来提高用户的访问效率和网站资源的利用率有一定的指导作用。 In order to identify the navigational patterns of web site visitors,Apriori algorithm is used to mine the user session file that has been generated after the data pre-processing process on the Web log file.It is desirable to interactively investigate web access data and patterns,to allow ad-hoc to discover and examine patterns which are not known.The association mining model can be used to generate the frequent itemsets that satisfy the minimum support threshold and strong association rules between selected pages that satisfy the both minimum confidence and minimum support thresholds.The association mining results have many guidelining roles for Web master to rearrange the web structure,provide recommendation service by predicting the web users navigational behaviour and improve the users web access efficiency and web resource utilization rate.
出处 《新疆农业大学学报》 CAS 北大核心 2011年第4期361-366,共6页 Journal of Xinjiang Agricultural University
基金 新疆维吾尔自治区电子信息发展专项资金项目(XJDZZXZJ20109)
关键词 用户访问序列文件 关联规则 最小支持度 最小置信度 user visiting sequence file association rule minimum confidence minimum support
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参考文献8

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