系统仿真学报 ›› 2017, Vol. 29 ›› Issue (5): 935-940.doi: 10.16182/j.issn1004731x.joss.201705001

• 仿真建模理论与方法 •    下一篇

一种基于高斯无向图的e-Learner情感调节模型

秦继伟1,2, 吐尔根·依布拉音2,*, 张辉国3   

  1. 1.新疆大学网络与技术中心,新疆 乌鲁木齐 830046;
    2.新疆多语种信息技术实验室,新疆 乌鲁木齐 830046;
    3.新疆大学数学与系统科学学院,新疆 乌鲁木齐 830046
  • 收稿日期:2016-03-23 修回日期:2016-08-29 出版日期:2017-05-08 发布日期:2020-06-03
  • 作者简介:秦继伟(1978-),女,河南,博士后,研究方向为智能网络学习,情感计算。
  • 基金资助:
    国家自然科学基金(61402392,61331911),中国博士后科学基金(2016M592867),国家重点基础研究规划项目(2014CB340506)

E-Learner's Emotion Regulation Model with Undirected Gaussian Graphical Model

Qin Jiwei1,2, Turgun·Ibragim2,*, Zhang Huiguo3   

  1. 1. Center of Network and Information Technology, Xinjiang University, Urumqi 830046, China;
    2. Xinjiang Laboratory of Multi-Language Infornation Technology, Xinjiang University, Urumqi 830046, China;
    3. College of Mathematics and System Sciences, Xinjiang University, Urumqi 830046, China
  • Received:2016-03-23 Revised:2016-08-29 Online:2017-05-08 Published:2020-06-03

摘要: 以e-Learning中学习者情感缺失问题为应用背景,针对目前已有情感调节模型中变量单一,对实际e-Learning环境中影响学习者情感变化的变量复杂、数据稀疏等适应能力支持不足的问题,提出基于高斯无向图的e-Learner情感调节模型,强调综合考虑影响学习者情感调节的多种属性,建立e-Learner的情感调节模型。在获取e-Learner实时学习日志的基础上,对影响e-Learner情感的主要因素,进行相关性分析、统计,利用高斯无向图模型拟合数据,理解数据变量间的相互关系,运用Chow-Liu 算法搜索最小BIC森林,得到e-Learner情感调节模型,为确定e-Learner情感调节的资源提供依据。

关键词: 情感, 情感调节, e-Learner, 高斯无向图

Abstract: Based on the absence of emotion in the background, e-Learner's emotion regulation model with simple variable can't fit the sparse and complex data in e-Learning, an e-Learner's emotion regulation model was proposed by Undirected Gaussian Graphical Model, which emphasized on many kinds of factor influences in emotion regulation. Correlation analysis, statistics, Gaussian undirected graph model fit the data to understand the relationship between data variables by using Chow-Liu algorithm, which searched for the smallest BIC forests and built e-learner's emotion regulation model based on the e-Learner's log. This model gives a basis for emotion regulation in e-Learning.

Key words: emotion, emotion regulation, e-Learner, Undirected Gaussian Graphical Model

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