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Automatically Classify Chinese Judgment Documents Utilizing Machine Learning Algorithms Read chapter Read first chapter

2017 | OriginalPaper | Chapter

DKG: An Expanded Knowledge Base for Online Course

Authors : Haimeng Duan, Yuanhao Zheng, Lei Shi, Changhong Jin, Hongwei Zeng, Jun Liu

Published in: Database Systems for Advanced Applications

Publisher: Springer International Publishing

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Abstract

Recent years have witnessed a proliferation of large-scale online education platforms. However, the learning materials provided by online courses are still finite. In this paper, to expand the learning materials on MOOC platforms, we construct an expanded knowledge base named DKG. DKG combines priori knowledge from concept map with extended textual fragments collected from web sources. For the sake of DKG’s quality, we also propose a supervised method with four novel features to evaluate the quality of textual fragments. Finally, we conduct experiments on four online courses. The results show that our method can find good textual fragments efficiently and expand learning materials successfully.

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previous chapter Predicting Honors Student Performance Using RBFNN and PCA Method
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Footnotes
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Metadata
Title
DKG: An Expanded Knowledge Base for Online Course
Authors
Haimeng Duan
Yuanhao Zheng
Lei Shi
Changhong Jin
Hongwei Zeng
Jun Liu
Copyright Year
2017
Book
Database Systems for Advanced Applications

Print ISBN: 978-3-319-55704-5

Electronic ISBN: 978-3-319-55705-2

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-55705-2_30

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