基于扩展元胞自动机的在线零售站点的自适应

Adaptive online retail Web site based on CA extended model

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。

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.