A Survey of Approaches to Automatic Question Generation:from 2019 to Early 2021

1059

Authors

nan

Abstract

AbstractTo provide analysis of recent researches of automatic question generation from text,we surveyed 9 papers between 2019 to early 2021, retrieved from Paper with Code(PwC). Our research follows the survey reported by Kurdi et al.(2020), in which analysis of 93 papers from 2014 to early2019 are provided. We analyzed the 9papers from aspects including: (1) purpose of question generation, (2) generation method, and (3) evaluation. We found that recent approaches tend to rely on semantic information and Transformer-based models are attracting increasing interest since they are more efficient. On the other hand,since there isn’t any widely acknowledged automatic evaluation metric designed for question generation, researchers adopt metrics of other natural language processing tasks to compare different systems.

Keywords

nan

Full Content

� �� Chao-Yi Lu Chingshin Academy Taipei, Taiwan chaoyilu.zoey@gmail.com Sin-En Lu Computer Science and Information Engineering National Central University Taoyuan, Taiwan alznn@g.ncu.edu.tw �� The 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021) Taoyuan, Taiwan, October 15-16, 2021. The Association for Computational Linguistics and Chinese Language Processing 151 �� …

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Publication Details

Paper ID:: 1059
Year:: 2021
Publication:: TIPSTER
Publication Type:: conf
DOI:: nan

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