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DKG: An Expanded Knowledge Base for Online Course

机译：DKG：在线课程的扩展知识库

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摘要

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.
机译：近年来，目睹了大型在线教育平台的泛滥。但是，在线课程提供的学习材料仍然有限。在本文中，为了扩展MOOC平台上的学习资料，我们构建了一个扩展的知识库，名为DKG。 DKG将概念图的先验知识与从Web来源收集的扩展文本片段结合在一起。为了确保DKG的质量，我们还提出了一种具有四个新颖功能的监督方法来评估文本片段的质量。最后，我们对四个在线课程进行了实验。结果表明，我们的方法可以有效地找到好的文本片段，并成功地扩展了学习材料。

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  • 来源
  • 会议地点 Suzhou(CN)
  • 作者

    Haimeng Duan; Yuanhao Zheng; Lei Shi; Changhong Jin; Hongwei Zeng; Jun Liu;

  • 作者单位

    SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Xi'an, China;

    SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Xi'an, China;

    SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Xi'an, China;

    SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Xi'an, China;

    SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Xi'an, China;

    SPKLSTN Lab, Department of Computer Science, Xi'an Jiaotong University, Xi'an, China;

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  • 正文语种 eng
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