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Sutskever, I., Vinyals, O. and Le, Q.V. Sequence to Sequence Learning with Neural Networks. Proceedings of the 27th International Conference on Neural Information Processing Systems, MIT Press, MA, 3104-3112.

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• TITLE: The Automatic Question Generation System for CET

  AUTHORS: Xinya Zhang, Xiaodong Yan, Zhou Yao

  KEYWORDS: Text Summarization, seq2seq Model, Attention Mechanism, College English Test

  JOURNAL NAME: Journal of Computer and Communications, Vol.9 No.9, September 30, 2021

  ABSTRACT: In this paper, we apply the abstractive text summarization technology to automatic generation system of reading comprehension, which is part of College English Test (CET) in China. At present, there is a growing demand of English reading examination questions, yet the manual examination question generating is time-consuming and labor-intensive. To relieve the pressure on question generating task, we put the related automatic technology into application, which aims to assist teachers in question generating, meanwhile, to provide more CET exercises for students. We combine seq2seq model and attention mechanism to generate the abstractive text summarization. The abstract generated by this method is easy to understand and in line with the question generating of long reading comprehension, the experiment showed good results of question generating.