利用主题模型识别学生在线讨论的优缺点

2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT) Pub Date : 2019-07-01 DOI:10.1109/ICALT.2019.00020

V. Rolim, R. F. Mello, Maverick Andre Dionisio Ferreira, Anderson Pinheiro Cavalcanti, Rinaldo Lima

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引用次数: 3

摘要

本文提出了一种基于潜狄利克雷分配(Latent Dirichlet Allocation, LDA)的基于主题模型的学生优缺点提取方法。我们的方法将从学生撰写的在线讨论论坛中提取的文本数据与维基百科等外部资源相结合。结果表明，基于学生在论坛中讨论的主题创建用户档案的方法是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Identifying Students' Weaknesses and Strengths Based on Online Discussion using Topic Modeling

This paper proposes a topic model-based approach to extract students' weaknesses and strength based on Latent Dirichlet Allocation (LDA). Our approach combines textual data extracted from online discussion forums written by students with external sources like Wikipedia. The results show the effectiveness of the proposed approach to create a user profile based on the topics covered by the students in discussion forums.

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2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)

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