TY - CHAP
T1 - Automatic Generation of E-Learning Contents Based on Deep Learning and Natural Language Processing Techniques
AU - Wang, Yiyi
AU - Okamura, Koji
N1 - Funding Information:
Acknowledgments. This research was supported by Strategic International Research Cooperative Program, Japan Science and Technology Agency (JST) SICORP Grant Number JPMJSC16H3 and JSPS KAKENHI Grant Number JP16K00480.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-030-39746-3_33
DO - 10.1007/978-3-030-39746-3_33
M3 - Chapter
AN - SCOPUS:85083458555
T3 - Lecture Notes on Data Engineering and Communications Technologies
SP - 311
EP - 322
BT - Lecture Notes on Data Engineering and Communications Technologies
PB - Springer Science and Business Media Deutschland GmbH
ER -