基于贝叶斯定理的个性化教务选课网站的研究

Personalized Educational Administration Chooses Class Web-site Based on Bayes Theorem

利用贝叶斯定理及其概率模型,结合过滤算法,对教务选课网站个性化设计进行研究,通过对用户以往访问的历史记录进行分析,予以推荐最新的内容,从而提高了用户的满意度,降低了用户浏览信息所消耗的时间,适应了用户的兴趣.

Most of the educational administration chooses class web-site have the problems like overload information and resource isotropic, so, it is a question of urgent personalized web-site design to be solved which needs to recommend useful information to them by analyzing the visitor＇s history records. In the paper some research on the personalization of web content recommendation by using Bayes theorem and Filter algorithm are made. It can recommend the latest information to web browsers and reduce the time spending on browsing the web, and adapt the interesting of them.