首页 | 本学科首页   官方微博 | 高级检索  
     

基于扩展元胞自动机的在线零售站点的自适应
引用本文:吴小兰,王忠群,刘涛,王勇.基于扩展元胞自动机的在线零售站点的自适应[J].计算机应用,2006,26(10):2430-2432.
作者姓名:吴小兰  王忠群  刘涛  王勇
作者单位:安徽工程科技学院,计算机科学与工程系,安徽,芜湖,241000
基金项目:安徽省教育厅自然科学基金
摘    要:在线零售业务中,用户须浏览许多无关页面,才能找到所需商品。解决该问题的一个思路是,建立隐马尔可夫模型(HMM)实现站点根据用户访问购买情况进行自适应。在隐马尔可夫模型初始化基础上,利用扩展元胞自动机理论,同样能实现站点自适应,且时间更短;并为基于扩展元胞自动机解决站点自适应问题提供了一个新思路。

关 键 词:Web数据挖掘  元胞自动机  自适应站点  隐马尔可夫模型
文章编号:1001-9081(2006)10-2430-03
收稿时间:2006-04-12
修稿时间:2006-04-122006-06-12

Adaptive online retail Web site based on CA extended model
WU Xiao-lan,WANG Zhong-qun,LIU Tao,WANG Yong.Adaptive online retail Web site based on CA extended model[J].journal of Computer Applications,2006,26(10):2430-2432.
Authors:WU Xiao-lan  WANG Zhong-qun  LIU Tao  WANG Yong
Affiliation:Department of Computer Science and Engineering, Anhui University of Technology and Science, Wuhu Anhui 241000, China
Abstract:In online retail, the conflict between the different interests of all customers to different commodities and the commodity classification structure of Web site will make most customers access overabundant Web pages. To solve the problem, building a Hidden Markov Model(HMM) to make the Web site adjust itself according to the users' visits to Web sites is one of the ways. Based on the initialization of hidden Markov Model, same results can be achieved by utilizing the theories of cellular automata extended model and less time was spent. This throws some light on the adaptation of Web site based on CA extended model.
Keywords:Web mining  cellular automata  adaptive Web site  Hidden Markov Model(HMM)
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《计算机应用》浏览原始摘要信息
点击此处可从《计算机应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号