吉林大学学报(信息科学版) ›› 2022, Vol. 40 ›› Issue (2): 288-294.

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基于 VEM 框架的教学资源共享平台设计

唐小娟   

  1. 长沙师范学院 信息科学与工程学院, 长沙 410100
  • 收稿日期:2021-05-26 出版日期:2022-06-11 发布日期:2022-06-12
  • 作者简介:唐小娟(1981— ), 女, 湖南武冈人, 长沙师范学院讲师, 主要从事教师教育和教育信息化研究, ( Tel)86-15874002364(E-mail)28051544@ qq. com.
  • 基金资助:
    湖南省教育厅科学研究基金资助项目(19C0138)

Design of Teaching Resource Sharing Platform Based on VEM Framework

TANG Xiaojuan   

  1. School of Information Science and Engineering, Changsha Normal University, Changsha 410100, China
  • Received:2021-05-26 Online:2022-06-11 Published:2022-06-12

摘要: 针对传统方法对教学资源的共享往往存在资源分类不明确、 共享效率低等问题, 提出了基于 VEM (Variational Expectation Maximization)框架的教学资源共享平台设计方案。 平台由对协同工作完成对教学资源 的预处理、 特征提取、 分类以及共享 4 个层次组成。 在预处理阶段, 删除冗余信息, 减少系统存储空间; 特征 提取模块运用语义邻接矩阵, 计算资源中词汇的特征度值, 挑选出特征度值较大的词汇; 在分类模块, 运用上 下位关系构建分类框架, 计算每个词对之间的关系强度, 根据强度的不同实现分类; 对完成分类的资源编号 分别存储, 教师可直接查找完成资源共享。 实验结果表明, 该教学资源共享平台的分类准确性为 98. 6% , 资源 共享平均用时为 1.15 s, 表明设计的教学资源共享平台的准确性和效率较高。

关键词: VEM 框架; , 教学资源共享; , 资源预处理; , 上下位关系; , 共享效率

Abstract: Traditional methods for the sharing of teaching resources often have problems such as unclear resource classification and low sharing efficiency. For this reason, a design scheme of teaching resource sharing platform based on the VEM ( Variational Expectation Maximization) framework is proposed. The platform consists of 4 levels, which are the preprocessing, feature extraction, classification and sharing of teaching resources for collaborative work. In the preprocessing stage, redundant information is deleted to reduce the system storage space. The feature extraction module uses the semantic adjacency matrix to calculate the feature value of the vocabulary in the resource, and selects the vocabulary with a larger feature value. In the classification module, the upper and lower relationship is used to construct a classification framework, calculate the strength of the relationship between each word pair, and realize the classification according to the different strength. The resource number of the completed classification is stored separately, and the teacher can directly find and complete the resource sharing. The experimental results show that the classification accuracy of the teaching resource sharing platform is 98. 6% , and the average time for resource sharing is 1.15 s, proving that the designed teaching resource sharing platform is accurate and efficient.

Key words: variational expectation maximization (VEM) framework; , sharing of teaching resources; , resource preprocessing; , the relationship between superior and subordinate; , sharing efficiency

中图分类号: 

  • TP311