摘要
随着因特网的成长,网络浏览使人们从本地或远程更方便地获取各种信息.网页数量的疯狂增长已经使得用户面对庞大的数据群无所适从,急需导航技术的帮助.一个新的马尔可夫链模型被引入用来跟踪所有团体成员的网页访问活动,并且推荐一些有用站点,引导人们更有效率地浏览网站.还提出一个基于半形式化过程描述的数据搜集算法,来获得有用数据,以推导出最好结果,并在原型系统中分析了代理服务器上的访问日志,对该算法进行描述.
With the growth of the Internet, World Wide Web increasingly helps people to make good use of rich information 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 new navigation approach, a modified Markov chain model is introduced, 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 semi-formal description of process is necessarily given for collecting desired data to gain top grade results The method is also illustrated by analyzing the proxy server's access log in the prototype system
出处
《计算机研究与发展》
EI
CSCD
北大核心
2005年第5期765-770,共6页
Journal of Computer Research and Development
基金
国家自然科学基金项目(69873035)
华南理工大学自然科学基金项目(G03E5041450)