隐马尔科夫模型在智能学习系统中的应用

计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (6): 178-180.

隐马尔科夫模型在智能学习系统中的应用

翟琳琳陈仪香

上海师范大学

收稿日期:2006-06-28 修回日期:1900-01-01 出版日期:2007-02-21 发布日期:2007-02-21
通讯作者: 翟琳琳

The application of HMM in Intelligent Learning System

Received:2006-06-28 Revised:1900-01-01 Online:2007-02-21 Published:2007-02-21

摘要/Abstract

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。本文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。

关键词: 智能学习 HMM 知识迁移 Baum-Welch算法

Abstract: 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

Key words: Intelligent Learning, HMM, Knowledge Transfer, Baum-Welch

翟琳琳陈仪香. 隐马尔科夫模型在智能学习系统中的应用[J]. 计算机工程与应用, 2007, 43(6): 178-180.