research-article

Generating Multi-hop Reasoning Questions to Improve Machine Reading Comprehension

Authors:

Jian YinAuthors Info & Claims

WWW '20: Proceedings of The Web Conference 2020

Pages 281 - 291

https://doi.org/10.1145/3366423.3380114

Published: 20 April 2020 Publication History

Abstract

This paper focuses on the topic of multi-hop question generation, which aims to generate questions needed reasoning over multiple sentences and relations to derive answers. In particular, we first build an entity graph to integrate various entities scattered over text based on their contextual relations. We then heuristically extract the sub-graph by the evidential relations and type, so as to obtain the reasoning chain and textual related contents for each question. Guided by the chain, we propose a holistic generator-evaluator network to form the questions, where such guidance helps to ensure the rationality of generated questions which need multi-hop deduction to correspond to the answers. The generator is a sequence-to-sequence model, designed with several techniques to make the questions syntactically and semantically valid. The evaluator optimizes the generator network by employing a hybrid mechanism combined of supervised and reinforced learning. Experimental results on HotpotQA data set demonstrate the effectiveness of our approach, where the generated samples can be used as pseudo training data to alleviate the data shortage problem for neural network and assist to learn the state-of-the-arts for multi-hop machine comprehension.

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https://doi.org/10.1007/s11280-024-01254-7
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Yuan WYin HHe TChen TWang QCui L(2022)Unified Question Generation with Continual Lifelong LearningProceedings of the ACM Web Conference 202210.1145/3485447.3511930(871-881)Online publication date: 25-Apr-2022
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Index Terms

Generating Multi-hop Reasoning Questions to Improve Machine Reading Comprehension
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
  2. Machine learning
2. Information systems

Index terms have been assigned to the content through auto-classification.

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Published In

cover image ACM Conferences

WWW '20: Proceedings of The Web Conference 2020

April 2020

3143 pages

ISBN:9781450370233

DOI:10.1145/3366423

Editors:
Yennun Huang
Acadmica sinica, Taiwan
,
Irwin King
The Chinese University of Hong Kong, Hong Kong
,
Tie-Yan Liu
Microsoft Research Asia, China
,
Maarten van Steen
University of Twente, Netherlands

Copyright © 2020 ACM.

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Published: 20 April 2020

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WWW '20: The Web Conference 2020

April 20 - 24, 2020

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Cited By

Zhou ZWan GPan SWu JHu WDu B(2024)Complex query answering over knowledge graphs foundation model using region embeddings on a lie groupWorld Wide Web10.1007/s11280-024-01254-727:3Online publication date: 11-Apr-2024
https://doi.org/10.1007/s11280-024-01254-7
Hou ZBi SQi GZheng YRen ZLi Y(2024)Syntax-guided question generation using prompt learningNeural Computing and Applications10.1007/s00521-024-09421-736:12(6271-6282)Online publication date: 26-Feb-2024
https://doi.org/10.1007/s00521-024-09421-7
Yuan WYin HHe TChen TWang QCui L(2022)Unified Question Generation with Continual Lifelong LearningProceedings of the ACM Web Conference 202210.1145/3485447.3511930(871-881)Online publication date: 25-Apr-2022
https://dl.acm.org/doi/10.1145/3485447.3511930
Su DXu PFung P(2022)QA4QG: Using Question Answering to Constrain Multi-Hop Question GenerationICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP43922.2022.9747008(8232-8236)Online publication date: 23-May-2022
https://doi.org/10.1109/ICASSP43922.2022.9747008
Yu JSu QQuan XYin J(2021)Multi-hop Reasoning Question Generation and Its ApplicationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2021.3073227(1-1)Online publication date: 2021
https://doi.org/10.1109/TKDE.2021.3073227
Yu JWang SYin J(2021)Adaptive Cross-Lingual Question Generation with Minimal ResourcesThe Computer Journal10.1093/comjnl/bxab106Online publication date: 19-Jul-2021
https://doi.org/10.1093/comjnl/bxab106

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