隐马尔科夫模型在智能学习系统中的应用  

Application of HMM in intelligent learning system

作　　者：翟琳琳[1] 陈仪香[1] 

机构地区：[1]上海师范大学数理信息学院,上海200234

出　　处：《计算机工程与应用》2007年第6期178-180,共3页Computer Engineering and Applications

基　　金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.60273054) ;高等院校博士学科点专项科研基金(the China Specialized Research Fund for the Doctoral Program of Higher Education under Grant No.20050270004);上海市教委科研基金(No.05DZ06) 。

摘　　要：智能学习系统中,用户希望在学习的过程中系统能够根据知识点之间的内在关系自动给出学习引导。要实现智能引导的功能,就要找到所有知识点之间的内在关联。使用大量学习记录作为训练集,建立隐马尔科夫模型,并且利用该模型得到最优观察序列,实现了知识点学习的智能引导。It is expected that intelligent learning system can automatically provide learning guidance for the learner in his learning process based on the patent relationship among the knowledges.To achieve this,it is necessary to find out the patent relationship between knowledges.This paper uses massive learning record as the training data,builds up HMM model and realizes the intelligent guidance.

关 键 词：智能学习 HMM 知识迁移 Baum-Welch算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]