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A Survey on Machine Reading Comprehension Systems
by
Baradaran, Razieh
, Ghiasi, Razieh
, Amirkhani, Hossein
in
Answers
/ Comprehension
/ Computational linguistics
/ Datasets
/ Deep learning
/ Extraction
/ Language
/ Machine learning
/ Natural language
/ Natural language processing
/ Neural networks
/ Polls & surveys
/ Problem solving
/ Reading comprehension
/ Survey Paper
/ Trends
2022
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A Survey on Machine Reading Comprehension Systems
by
Baradaran, Razieh
, Ghiasi, Razieh
, Amirkhani, Hossein
in
Answers
/ Comprehension
/ Computational linguistics
/ Datasets
/ Deep learning
/ Extraction
/ Language
/ Machine learning
/ Natural language
/ Natural language processing
/ Neural networks
/ Polls & surveys
/ Problem solving
/ Reading comprehension
/ Survey Paper
/ Trends
2022
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Do you wish to request the book?
A Survey on Machine Reading Comprehension Systems
by
Baradaran, Razieh
, Ghiasi, Razieh
, Amirkhani, Hossein
in
Answers
/ Comprehension
/ Computational linguistics
/ Datasets
/ Deep learning
/ Extraction
/ Language
/ Machine learning
/ Natural language
/ Natural language processing
/ Neural networks
/ Polls & surveys
/ Problem solving
/ Reading comprehension
/ Survey Paper
/ Trends
2022
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Journal Article
A Survey on Machine Reading Comprehension Systems
2022
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Overview
Machine Reading Comprehension (MRC) is a challenging task and hot topic in Natural Language Processing. The goal of this field is to develop systems for answering the questions regarding a given context. In this paper, we present a comprehensive survey on diverse aspects of MRC systems, including their approaches, structures, input/outputs, and research novelties. We illustrate the recent trends in this field based on a review of 241 papers published during 2016–2020. Our investigation demonstrated that the focus of research has changed in recent years from answer extraction to answer generation, from single- to multi-document reading comprehension, and from learning from scratch to using pre-trained word vectors. Moreover, we discuss the popular datasets and the evaluation metrics in this field. The paper ends with an investigation of the most-cited papers and their contributions.
Publisher
Cambridge University Press
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