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MINING LEARNERS' TOPIC INTERESTS IN COURSE REVIEWS BASED ON LIKE-LDA MODEL

机译:基于LIKE-LDA模型的矿业学习者在课程审查中的兴趣

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摘要

The diversity and volume of textual data in the course reviews area are overwhelming. These data offer faculties with a chance to capture topic interests of learners and further make relevant recommendations for them. "Like" or "+1" considered as a specific interactive means among learners has been commonly applied to enriching the interactivity and flexibility of online community. This information can reflect their supporting, appreciation for the textual contents and topical interests. In view of this situation, the topic model by incorporating the behavioral feature "like", namely Like-Latent Dirichlet Allocation (Like-LDA), is proposed to detect the latent topic interests in course reviews. The experimental results on the real-life dataset show that, Like-LDA can gain better performance in extracting the new hidden topics, higher accuracy of topic detection and words coherency in each topic than LDA.
机译:课程评论区域中文本数据的多样性和数量是压倒性的。这些数据为教师提供了捕捉学习者的主题兴趣并进一步为他们提供相关建议的机会。作为学习者之间特定的交互方式的“喜欢”或“ +1”已普遍用于丰富在线社区的交互性和灵活性。这些信息可以反映出他们对文本内容和主题兴趣的支持,欣赏。鉴于这种情况,提出了通过结合行为特征“喜欢”的主题模型,即喜欢-潜在狄利克雷分配(Like-LDA),来检测课程复习中潜在的主题兴趣。在真实数据集上的实验结果表明,与LDA相比,Like-LDA在提取新的隐藏主题方面具有更好的性能,主题检测的准确性更高,每个主题中的单词连贯性更高。

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  • 作者单位

    National Engineering Research Center for E-Learning Central China Normal University-No. 152, Luoyu Road, Wuhan 430079, P. R. China;

    National Engineering Research Center for E-Learning Central China Normal University-No. 152, Luoyu Road, Wuhan 430079, P. R. China;

    National Engineering Research Center for E-Learning Central China Normal University-No. 152, Luoyu Road, Wuhan 430079, P. R. China;

    National Engineering Research Center for E-Learning Central China Normal University-No. 152, Luoyu Road, Wuhan 430079, P. R. China;

    National Engineering Research Center for E-Learning Central China Normal University-No. 152, Luoyu Road, Wuhan 430079, P. R. China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Topic interests; Topic modeling; LDA; Like; Course reviews;

    机译:主题兴趣;主题建模;LDA;喜欢;课程评论;

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