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An Enhanced Convolutional Neural Network Model for Answer Selection

Authors:

Jiahui Guo,

Bin Yue,

Guandong Xu,

Zhenglu Yang,

Jin-Mao WeiAuthors Info & Claims

WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion

Pages 789 - 790

https://doi.org/10.1145/3041021.3054216

Published: 03 April 2017 Publication History

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Abstract

Answer selection is an important task in question answering (QA) from the Web. To address the intrinsic difficulty in encoding sentences with semantic meanings, we introduce a general framework, i.e., Lexical Semantic Feature based Skip Convolution Neural Network (LSF-SCNN), with several optimization strategies. The intuitive idea is that the granular representations with more semantic features of sentences are deliberately designed and estimated to capture the similarity between question-answer pairwise sentences. The experimental results demonstrate the effectiveness of the proposed strategies and our model outperforms the state-of-the-art ones by up to 3.5% on the metrics of MAP and MRR.

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Cited By

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Yue YPeng YWang D(2023)Deep Learning Short Text Sentiment Analysis Based on Improved Particle Swarm OptimizationElectronics10.3390/electronics1219411912:19(4119)Online publication date: 2-Oct-2023
https://doi.org/10.3390/electronics12194119
Tang Y(2023)An innovative training model for developing talents in French language education based on the deep learning modelApplied Mathematics and Nonlinear Sciences10.2478/amns.2023.1.004679:1Online publication date: 29-Jun-2023
https://doi.org/10.2478/amns.2023.1.00467
Kumar SChauhan A(2022)Augmenting Textbooks with cQA Question-Answers and Annotated YouTube Videos to Increase Its RelevanceNeural Processing Letters10.1007/s11063-022-10897-455:1(551-588)Online publication date: 30-Jun-2022
https://doi.org/10.1007/s11063-022-10897-4
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Index Terms

An Enhanced Convolutional Neural Network Model for Answer Selection
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Question answering

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Published In

WWW '17 Companion: Proceedings of the 26th International Conference on World Wide Web Companion

April 2017

1738 pages

ISBN:9781450349147

General Chairs:
Rick Barrett
W3Events
,
Rick Cummings
Murdoch University
,
Program Chairs:
Eugene Agichtein
Emory University
,
Evgeniy Gabrilovich
Google Research

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

International World Wide Web Conferences Steering Committee

Republic and Canton of Geneva, Switzerland

Publication History

Published: 03 April 2017

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Funding Sources

Research Fund for International Young Scientists
Ministry of Education of Humanities and Social Science Project
Natural Science Foundation of Tianjin City
Science Foundation of China

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WWW '17

Sponsor:

IW3C2

WWW '17: 26th International World Wide Web Conference

April 3 - 7, 2017

Perth, Australia

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WWW '17 Companion Paper Acceptance Rate 164 of 966 submissions, 17%;

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Yue YPeng YWang D(2023)Deep Learning Short Text Sentiment Analysis Based on Improved Particle Swarm OptimizationElectronics10.3390/electronics1219411912:19(4119)Online publication date: 2-Oct-2023
https://doi.org/10.3390/electronics12194119
Tang Y(2023)An innovative training model for developing talents in French language education based on the deep learning modelApplied Mathematics and Nonlinear Sciences10.2478/amns.2023.1.004679:1Online publication date: 29-Jun-2023
https://doi.org/10.2478/amns.2023.1.00467
Kumar SChauhan A(2022)Augmenting Textbooks with cQA Question-Answers and Annotated YouTube Videos to Increase Its RelevanceNeural Processing Letters10.1007/s11063-022-10897-455:1(551-588)Online publication date: 30-Jun-2022
https://doi.org/10.1007/s11063-022-10897-4
Jin ZZhang BZhou FQin JYin X(2020)Ranking via partial ordering for answer selectionInformation Sciences10.1016/j.ins.2020.05.110538(358-371)Online publication date: Oct-2020
https://doi.org/10.1016/j.ins.2020.05.110
Der Weth CAbdul AKashyap AKankanhalli M(2019)CloseUp—A Community-Driven Live Online Search EngineACM Transactions on Internet Technology10.1145/330144219:3(1-21)Online publication date: 27-Aug-2019
https://dl.acm.org/doi/10.1145/3301442
Zhang PHuang XLi M(2019)Disease Prediction and Early Intervention System Based on Symptom Similarity AnalysisIEEE Access10.1109/ACCESS.2019.29578167(176484-176494)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2957816
Zhu LLong JZhang CYu WYuan XSun L(2019)An Efficient Approach for Geo-Multimedia Cross-Modal RetrievalIEEE Access10.1109/ACCESS.2019.29400557(180571-180589)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2940055
Kumar GHenderson MChan SNguyen HNgoo L(2019)Question-Answer Selection in User to User Marketplace Conversations9th International Workshop on Spoken Dialogue System Technology10.1007/978-981-13-9443-0_35(397-403)Online publication date: 25-Sep-2019
https://doi.org/10.1007/978-981-13-9443-0_35

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Length-adaptive Neural Network for Answer Selection

Recurrent convolutional neural network for answer selection in community question answering

Noise-Contrastive Estimation for Answer Selection with Deep Neural Networks

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