Extract Concept using Subtitles in MOOC

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS(2022)

引用 0|浏览11
暂无评分
摘要
Massive open online courses (MOOCs) are a variety of courses offered through the online mode, paid or unpaid and has evolved as an excellent learning resource for students. The structure of the course design is mainly linear where there are a few video lectures provided by either professors of several universities, or people with expertise in the particular subject. They are usually graded on a weekly basis through quizzes or peer-graded assignments. The objective of this paper is to extract the concepts taught in the videos from the subtitles, which could later be used to enhance recommendations of the learners using their clickstream data. The teachers could also use this to see the demand for their courses. Evaluate two keyword extraction methods, which are BERT and LDA using different Coursera courses. The experimental results show that BERT outperforms LDA in terms of Coherence.
更多
查看译文
关键词
LDA, BERT, topic coherence, overlap coefficient
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要