Multi-label Classification and Prediction of Tags for Online Platform Questions

نویسنده

  • Yeeleng Scott Vang
چکیده

Past studies have shown personalized tutoring offers students the best means to master new concepts. The current open online course (MOOC) platforms offer various means for instructors to interact with students from vote-polling to Q&A-style format. In this project, a multi-label supervised classification framework is used to classify questions posted in a Q&A-style platform to predict the appropriate tags based on the text of the title and body alone.

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تاریخ انتشار 2013