情感学习中基于检测眨眼频率和贝叶斯网络的情感分类算法

计算机科学 ›› 2013, Vol. 40 ›› Issue (12): 287-291.

情感学习中基于检测眨眼频率和贝叶斯网络的情感分类算法

陶小梅,牛秦洲

桂林理工大学信息科学与工程学院桂林541004;桂林理工大学信息科学与工程学院桂林541004

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金项目(51365010),广西高等学校立项科研项目(201204LX177)资助

Emotion Classification Algorithm Based on Blink Frequency Detection and Bayesian Network in Affective Learning

TAO Xiao-mei and NIU Qin-zhou

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 针对情感学习中常用情感状态识别方法的局限性,研究了一种通过检测学习者眨眼频率来对学习过程中产生的情感状态进行分类的方法。该方法首先根据学习者的眨眼频率将其情感状态分为正向情感或者负向情感,然后再通过贝叶斯网络根据学生信息及教学活动的上下文信息将负向情感进一步解析为具体的负向情感状态。将该分类算法应用到一个以教学视频为主体学习资源的电子学习平台,以验证其有效性。

关键词: 眨眼检测,贝叶斯网络,情感分类,情感学习

Abstract: This paper explored an emotional state classification algorithm through detecting the learner’s blink frequency during a learning process．This algorithm could classify the learner’s emotional states into positive emotional state and negative emotional state．And the negative emotional categories could be inferred by a Bayesian network using the parameters about the student’s personal information and the learning context information．An e-learning system using instructional videos as the core learning material was developed to validate this classification algorithm．

Key words: Blink detection,Bayesian network,Emotion classification,Affective learning

陶小梅,牛秦洲. 情感学习中基于检测眨眼频率和贝叶斯网络的情感分类算法[J]. 计算机科学, 2013, 40(12): 287-291. https://doi.org/

TAO Xiao-mei and NIU Qin-zhou. Emotion Classification Algorithm Based on Blink Frequency Detection and Bayesian Network in Affective Learning[J]. Computer Science, 2013, 40(12): 287-291. https://doi.org/

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