Adaptive online retail Web site based on CA extended model
基于扩展元胞自动机的在线零售站点的自适应

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.