Study on Text Classification of MOOC Course Comments Based on Chinese Character level Convolutional Networks
With the rise of the educational big data and the development of MOOCs, a wide range of comments have come up. Now most of the existing MOOCs text classification models are for small scale comments, and fail to extract high level abstract information among characters. In this paper, crawler technology is used to crawl the comment data in MOOCs forums comprehensively, and a character table containing 5500 comment data is constructed then. In terms of word embedding operation, a text classification model of MOOCs comment data based on Chinese character level convolutional neural network is proposed to avoid the pre training process of word vector. The experiments show that our model could improve the classification accuracy comparing with traditional methods.
2018 International Computers, Signals and Systems Conference (ICOMSSC)