A Novel Framework for Automatic Chinese Question Generation Based on Multi-Feature Neural Network Model

Hai-Tao Zheng1, Jinxin Han1, Jinyuan Chen1 and Arun Kumar Sangaiah2

  1. Graduate School at Shenzhen Tsinghua University
    China, Shenzhen 518055
    zheng.haitao@sz.tsinghua.edu.cn, {hanjx16,cj-chen13}@mails.tsinghua.edu.cn
  2. School of Computing Science and Engineering VIT University
    India, Tamil Nadu Vellore-632014
    sarunkumar@vit.ac.in

Abstract

Automatic question generation from text or paragraph is a great challenging task which attracts broad attention in natural language processing. Because of the verbose texts and fragile ranking methods, the quality of top generated questions is poor. In this paper, we present a novel framework Automatic Chinese Question Generation (ACQG) to generate questions from text or paragraph. In ACQG, we use an adopted TextRank to extract key sentences and a template-based method to construct questions from key sentences. Then a multi-feature neural network model is built for ranking to obtain the top questions. The automatic evaluation result reveals that the proposed framework outperforms the state-of-the-art systems in terms of perplexity. In human evaluation, questions generated by ACQG rate a higher score.

Key words

Chinese Question Generation, TextRank, Multi-Feature Neural Network Model

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS171121018Z

Publication information

Volume 15, Issue 3 (October 2018)
Year of Publication: 2018
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Zheng, H., Han, J., Chen, J., Sangaiah, A. K.: A Novel Framework for Automatic Chinese Question Generation Based on Multi-Feature Neural Network Model. Computer Science and Information Systems, Vol. 15, No. 3, 487–499. (2018), https://doi.org/10.2298/CSIS171121018Z