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

作　　者：米娜瓦尔.努拉合买提 玛依拉.别克强塔依娃 张太红[1] 曾明[2] Osmar R.Zaiane 

机构地区：[1]新疆农业大学计算机与信息工程学院,乌鲁木齐830052 [2]西安交通大学软件学院,西安710049 [3]加拿大阿尔伯塔大学计算机科学系

出　　处：《新疆农业大学学报》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)

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.

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 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]