research-article

Deep Learning Approaches to Semantic Relevance Modeling for Chinese Question-Answer Pairs

Authors:

Deyuan ZhangAuthors Info & Claims

ACM Transactions on Asian Language Information Processing (TALIP), Volume 10, Issue 4

Article No.: 21, Pages 1 - 16

https://doi.org/10.1145/2025384.2025389

Published: 01 December 2011 Publication History

Abstract

The human-generated question-answer pairs in the Web social communities are of great value for the research of automatic question-answering technique. Due to the large amount of noise information involved in such corpora, it is still a problem to detect the answers even though the questions are exactly located. Quantifying the semantic relevance between questions and their candidate answers is essential to answer detection in social media corpora. Since both the questions and their answers usually contain a small number of sentences, the relevance modeling methods have to overcome the problem of word feature sparsity. In this article, the deep learning principle is introduced to address the semantic relevance modeling task. Two deep belief networks with different architectures are proposed by us to model the semantic relevance for the question-answer pairs. According to the investigation of the textual similarity between the community-driven question-answering (cQA) dataset and the forum dataset, a learning strategy is adopted to promote our models’ performance on the social community corpora without hand-annotating work. The experimental results show that our method outperforms the traditional approaches on both the cQA and the forum corpora.

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Cited By

Omondiagbe OLicorish SMacdonell S(2022)Evaluating Simple and Complex Models’ Performance When Predicting Accepted Answers on Stack Overflow2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA56994.2022.00014(29-38)Online publication date: Aug-2022
https://doi.org/10.1109/SEAA56994.2022.00014
Li RChen GZhu TLiu ZXiong Y(2021)Recognizing Named Entity in Electric Power DocumentsAdvances in Natural Computation, Fuzzy Systems and Knowledge Discovery10.1007/978-3-030-70665-4_71(652-660)Online publication date: 27-Jun-2021
https://doi.org/10.1007/978-3-030-70665-4_71
Xu BZhuge H(2020)The influence of semantic link network on the ability of question-answering systemFuture Generation Computer Systems10.1016/j.future.2020.02.042108(1-14)Online publication date: Jul-2020
https://doi.org/10.1016/j.future.2020.02.042
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Index Terms

Deep Learning Approaches to Semantic Relevance Modeling for Chinese Question-Answer Pairs
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources

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Published In

cover image ACM Transactions on Asian Language Information Processing

ACM Transactions on Asian Language Information Processing Volume 10, Issue 4

December 2011

112 pages

ISSN:1530-0226

EISSN:1558-3430

DOI:10.1145/2025384

Issue’s Table of Contents

Copyright © 2011 ACM.

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: 01 December 2011

Accepted: 01 April 2011

Revised: 01 February 2011

Received: 01 November 2010

Published in TALIP Volume 10, Issue 4

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Fundamental Research Funds for the Central Universities
National Natural Science Foundation of China

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Cited By

Omondiagbe OLicorish SMacdonell S(2022)Evaluating Simple and Complex Models’ Performance When Predicting Accepted Answers on Stack Overflow2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)10.1109/SEAA56994.2022.00014(29-38)Online publication date: Aug-2022
https://doi.org/10.1109/SEAA56994.2022.00014
Li RChen GZhu TLiu ZXiong Y(2021)Recognizing Named Entity in Electric Power DocumentsAdvances in Natural Computation, Fuzzy Systems and Knowledge Discovery10.1007/978-3-030-70665-4_71(652-660)Online publication date: 27-Jun-2021
https://doi.org/10.1007/978-3-030-70665-4_71
Xu BZhuge H(2020)The influence of semantic link network on the ability of question-answering systemFuture Generation Computer Systems10.1016/j.future.2020.02.042108(1-14)Online publication date: Jul-2020
https://doi.org/10.1016/j.future.2020.02.042
Herrera JParra DPoblete B(2020)Social QA in non-CQA platformsFuture Generation Computer Systems10.1016/j.future.2019.12.023105:C(631-649)Online publication date: 1-Apr-2020
https://dl.acm.org/doi/10.1016/j.future.2019.12.023
Zhou GZhou YHe TWu W(2019)Learning semantic representation with neural networks for community question answering retrievalKnowledge-Based Systems10.1016/j.knosys.2015.11.00293:C(75-83)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1016/j.knosys.2015.11.002
Li WLi WWu YMcIlraith SWeinberger K(2018)A unified model for document-based question answering based on human-like reading strategyProceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence10.5555/3504035.3504110(604-611)Online publication date: 2-Feb-2018
https://dl.acm.org/doi/10.5555/3504035.3504110
Su MWu CHuang KLin W(2018)Response Selection and Automatic Message-Response Expansion in Retrieval-Based QA Systems using Semantic Dependency Pair ModelACM Transactions on Asian and Low-Resource Language Information Processing10.1145/322918418:1(1-24)Online publication date: 12-Nov-2018
https://dl.acm.org/doi/10.1145/3229184
Ghosh KBhowmick PGoyal PSheth ANgonga AWang yChang EŚlęzak DFranczyk BAlt RTao X(2017)Using re-ranking to boost deep learning based community question retrievalProceedings of the International Conference on Web Intelligence10.1145/3106426.3106442(807-814)Online publication date: 23-Aug-2017
https://dl.acm.org/doi/10.1145/3106426.3106442
Li JZhang TLuo WYang JYuan XZhang J(2017)Sparseness Analysis in the Pretraining of Deep Neural NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2016.254168128:6(1425-1438)Online publication date: Jun-2017
https://doi.org/10.1109/TNNLS.2016.2541681
Zhou GHuang J(2017)Modeling and Learning Distributed Word Representation with Metadata for Question RetrievalIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.266562529:6(1226-1239)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1109/TKDE.2017.2665625
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