Automatic Generation of E-Learning Contents Based on Deep Learning and Natural Language Processing Techniques

Yiyi Wang, Koji Okamura

研究成果: Chapter in Book/Report/Conference proceedingChapter

1 引用 (Scopus)

抜粋

With the development of automation in all industries, E-Learning automation: automatically generate E-Learning contents gives E-Learning teachers new opportunities to implement effective management of E-Learning systems. And many eLearning professionals already use E-Learning templates and online asset libraries to create cost effective eLearning courses. Moreover, all E-Learning Automation methods have one thing in common—algorithms: used to control various aspects of e-learning course creation. Additionally, another important thing is online exams which are used to get an immediate feedback from learners. This research focuses on automation generation of E-Learning contents, which can be mainly divided into three parts. Firstly, automatically summarize relevant documents using natural language processing and deep learning techniques. Secondly, detecting keywords in generated summaries and then delete them from input summaries. Finally, rearrange output results and fill them into E-Learning system.

元の言語英語
ホスト出版物のタイトルLecture Notes on Data Engineering and Communications Technologies
出版者Springer
ページ311-322
ページ数12
DOI
出版物ステータス出版済み - 1 1 2020

出版物シリーズ

名前Lecture Notes on Data Engineering and Communications Technologies
47
ISSN(印刷物)2367-4512
ISSN(電子版)2367-4520

All Science Journal Classification (ASJC) codes

  • Media Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computer Networks and Communications
  • Information Systems

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  • これを引用

    Wang, Y., & Okamura, K. (2020). Automatic Generation of E-Learning Contents Based on Deep Learning and Natural Language Processing Techniques. : Lecture Notes on Data Engineering and Communications Technologies (pp. 311-322). (Lecture Notes on Data Engineering and Communications Technologies; 巻数 47). Springer. https://doi.org/10.1007/978-3-030-39746-3_33