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Bi-directional Long Short-Term Memory Model with Semantic Positional Attention for the Question Answering System

Authors:

Qingchuan Zhang,

Qingyu JinAuthors Info & Claims

Transactions on Asian and Low-Resource Language Information Processing, Volume 20, Issue 5

Article No.: 77, Pages 1 - 13

https://doi.org/10.1145/3439800

Published: 30 June 2021 Publication History

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Abstract

The intelligent question answering system aims to provide quick and concise feedback on the questions of users. Although the performance of phrase-level and numerous attention models have been improved, the sentence components and position information are not emphasized enough. This article combines Ci-Lin and word2vec to divide all of the words in the question-answer pairs into groups according to the semantics and select one kernel word in each group. The remaining words are common words and realize the semantic mapping mechanism between kernel words and common words. With this Chinese semantic mapping mechanism, the common words in all questions and answers are replaced by the semantic kernel words to realize the normalization of the semantic representation. Meanwhile, based on the bi-directional LSTM model, this article introduces a method of the combination of semantic role labeling and positional context, dividing the sentence into multiple semantic segments according to semantic logic. The weight is given to the neighboring words in the same semantic segment and propose semantic role labeling position attention based on the bi-directional LSTM model (BLSTM-SRLP). The good performance of the BLSTM-SRLP model has been demonstrated in comparative experiments on the food safety field dataset (FS-QA).

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Cited By

Al-Selwi SHassan MAbdulkadir SMuneer ASumiea EAlqushaibi ARagab M(2024)RNN-LSTMJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2024.10206836:5Online publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1016/j.jksuci.2024.102068
Ahmed MKhan HIqbal TKhaled Alarfaj FAlomair AAlmusallam N(2023)On solving textual ambiguities and semantic vagueness in MRC based question answering using generative pre-trained transformersPeerJ Computer Science10.7717/peerj-cs.14229(e1422)Online publication date: 24-Jul-2023
https://doi.org/10.7717/peerj-cs.1422
Rehman MRaghuvanshi DKumar N(2023)KisanQRSComputers and Electronics in Agriculture10.1016/j.compag.2023.108180213:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.compag.2023.108180
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Index Terms

Bi-directional Long Short-Term Memory Model with Semantic Positional Attention for the Question Answering System
1. Theory of computation
  1. Logic
    1. Automated reasoning

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Information & Contributors

Information

Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 20, Issue 5

September 2021

320 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3467024

Editor:
Imed Zitouni
Google, USA

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Copyright © 2021 Association for Computing Machinery.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 June 2021

Accepted: 01 November 2020

Revised: 01 November 2020

Received: 01 August 2020

Published in TALLIP Volume 20, Issue 5

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National Key Technology R&D Program of China
National Natural Science Foundation of China
Beijing Natural Science Foundation

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Cited By

Al-Selwi SHassan MAbdulkadir SMuneer ASumiea EAlqushaibi ARagab M(2024)RNN-LSTMJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2024.10206836:5Online publication date: 24-Jul-2024
https://dl.acm.org/doi/10.1016/j.jksuci.2024.102068
Ahmed MKhan HIqbal TKhaled Alarfaj FAlomair AAlmusallam N(2023)On solving textual ambiguities and semantic vagueness in MRC based question answering using generative pre-trained transformersPeerJ Computer Science10.7717/peerj-cs.14229(e1422)Online publication date: 24-Jul-2023
https://doi.org/10.7717/peerj-cs.1422
Rehman MRaghuvanshi DKumar N(2023)KisanQRSComputers and Electronics in Agriculture10.1016/j.compag.2023.108180213:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.compag.2023.108180
Lei LYuan GZhang TYu H(2022)Low-Power Feature-Attention Chinese Keyword Spotting Framework with Distillation LearningACM Transactions on Asian and Low-Resource Language Information Processing10.1145/355800222:2(1-14)Online publication date: 27-Dec-2022
https://dl.acm.org/doi/10.1145/3558002
Bi MLiu XZhang QYang Z(2022)Machine reading comprehension combined with semantic dependency for Chinese zero pronoun resolutionArtificial Intelligence Review10.1007/s10462-022-10364-556:8(7597-7612)Online publication date: 15-Dec-2022
https://dl.acm.org/doi/10.1007/s10462-022-10364-5

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