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Noise-Contrastive Estimation for Answer Selection with Deep Neural Networks

Authors:

Jimmy LinAuthors Info & Claims

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Pages 1913 - 1916

https://doi.org/10.1145/2983323.2983872

Published: 24 October 2016 Publication History

Abstract

We study answer selection for question answering, in which given a question and a set of candidate answer sentences, the goal is to identify the subset that contains the answer. Unlike previous work which treats this task as a straightforward pointwise classification problem, we model this problem as a ranking task and propose a pairwise ranking approach that can directly exploit existing pointwise neural network models as base components. We extend the Noise-Contrastive Estimation approach with a triplet ranking loss function to exploit interactions in triplet inputs over the question paired with positive and negative examples. Experiments on TrecQA and WikiQA datasets show that our approach achieves state-of-the-art effectiveness without the need for external knowledge sources or feature engineering.

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Cited By

Li QYao NZhou NZhao J(2025)Entity and relationship extraction based on span contribution evaluation and focusing frameworkComputer Speech and Language10.1016/j.csl.2024.10174490:COnline publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1016/j.csl.2024.101744
Zheng CJiang GYan XYin PZhou QCheng J(2024)GE2: A General and Efficient Knowledge Graph Embedding Learning SystemProceedings of the ACM on Management of Data10.1145/36549862:3(1-27)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3654986
Yang ZDing MHuang TCen YSong JXu BDong YTang J(2024)Does Negative Sampling Matter? a Review With Insights Into its Theory and ApplicationsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.337147346:8(5692-5711)Online publication date: Aug-2024
https://doi.org/10.1109/TPAMI.2024.3371473
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Index Terms

Noise-Contrastive Estimation for Answer Selection with Deep Neural Networks
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Ranking
    2. Machine learning approaches
      1. Neural networks
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Question answering

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cover image ACM Conferences

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

October 2016

2566 pages

ISBN:9781450340731

DOI:10.1145/2983323

General Chairs:
Snehasis Mukhopadhyay
Indiana University Purdue University Indianapolis, USA
,
ChengXiang Zhai
University of Illinois at Urbana-Champaign, USA
,
Program Chairs:
Elisa Bertino
Purdue University
,
Fabio Crestani
University of Lugano
,
Javed Mostafa
University of North Carolina
,
Jie Tang
Tsinghua University
,
Luo Si
Alibaba Group Inc & Purdue University
,
Xiaofang Zhou
University of Queensland
,
Yi Chang
Yahoo Research
,
Yunyao Li
IBM Research - Almaden
,
Parikshit Sondhi
WalmartLabs

Copyright © 2016 ACM.

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Published: 24 October 2016

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October 24 - 28, 2016

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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https://dl.acm.org/doi/10.1016/j.csl.2024.101744
Zheng CJiang GYan XYin PZhou QCheng J(2024)GE2: A General and Efficient Knowledge Graph Embedding Learning SystemProceedings of the ACM on Management of Data10.1145/36549862:3(1-27)Online publication date: 30-May-2024
https://dl.acm.org/doi/10.1145/3654986
Yang ZDing MHuang TCen YSong JXu BDong YTang J(2024)Does Negative Sampling Matter? a Review With Insights Into its Theory and ApplicationsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.337147346:8(5692-5711)Online publication date: Aug-2024
https://doi.org/10.1109/TPAMI.2024.3371473
Pang SZeng YZhao JXue J(2024)A Mutually Textual and Visual Refinement Network for Image-Text MatchingIEEE Transactions on Multimedia10.1109/TMM.2024.336996826(7555-7566)Online publication date: 26-Feb-2024
https://dl.acm.org/doi/10.1109/TMM.2024.3369968
Maia MEndres M(2024)Investigating Questioner’s Explicit Information Influences in Transformer-based Community Question Answering2024 IEEE 18th International Conference on Semantic Computing (ICSC)10.1109/ICSC59802.2024.00021(93-100)Online publication date: 5-Feb-2024
https://doi.org/10.1109/ICSC59802.2024.00021
Abdul Hakim ZHaque Sarker NSingh RPaul BDabouei AXu M(2024)Leveraging Generative Language Models for Weakly Supervised Sentence Component Analysis in Video-Language Joint Learning2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW63382.2024.00203(1975-1985)Online publication date: 17-Jun-2024
https://doi.org/10.1109/CVPRW63382.2024.00203
Huang DTu S(2024)MulMol: Transformer-based Multi-Task Molecular Representation Learning2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)10.1109/BIBM62325.2024.10822716(681-686)Online publication date: 3-Dec-2024
https://doi.org/10.1109/BIBM62325.2024.10822716
Xu YZhao XSong XWang BYu T(2024)Boosting Protein Language Models with Negative Sample MiningMachine Learning and Knowledge Discovery in Databases. Applied Data Science Track10.1007/978-3-031-70381-2_13(199-214)Online publication date: 22-Aug-2024
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Liu SZhou GXia YWu HLi Z(2023)A data-centric way to improve entity linking in knowledge-based question answeringPeerJ Computer Science10.7717/peerj-cs.12339(e1233)Online publication date: 9-Feb-2023
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Zhang YZhao CLiao WZhou WYuan M(2023)Asymmetrical Attention Networks Fused Autoencoder for Debiased RecommendationACM Transactions on Intelligent Systems and Technology10.1145/359649814:6(1-24)Online publication date: 14-Nov-2023
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