Associated navigation on the Web according to users´ activities

Although with the growth of Internet, World Wide Web increasingly helps people to make good use of rich information no matter from local or remote site, the amount of Web pages is so enormous that users are destined to drown in the huge data of the Web without any navigation. To provide a navigation approach, this paper introduces a modified Markov chain model which utilizes all group members´ traces in the Web to recommend some potential useful Web sites and navigates people when they browse Web pages, while users´ activities react to the model. Before that, an algorithm based on a semiformal description of process is necessarily given for collecting desired data to gain top grade results. We also illustrate the method by analyzing the proxy server´s access log in our prototype system.