摘要： 针对在线零售业务系统中用户要进入许多无关页面才能找到所需商品的问题，站点应能根据群体用户购买兴趣动态调整网页分配，即站点自适应。借用PageRank算法对元胞自动机模型进行改进，实现站点的自适应调整。与原模型相比，改进模型的演化规则简单、时间复杂度低、性能更优越。

关键词: 元胞自动机, PageRank算法, Web数据挖掘, 自适应站点

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 customers access overabundant Web pages. To solve this problem, the data about the customers’ interests are mined to make the Web site adjust its structure, which is adaptive site. Based on improvement of the cellular automaton model using the PageRank algorithm, it achieves the adaptive adjustment and spents less time.

Key words: Cellular Automata(CA), PageRank algorithm, Web data mining, adaptive site

中图分类号: 

• TP311