short-paper

Text Coherence Analysis Based on Deep Neural Network

Authors:

Zhongfei ZhangAuthors Info & Claims

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

Pages 2027 - 2030

https://doi.org/10.1145/3132847.3133047

Published: 06 November 2017 Publication History

Abstract

In this paper, we propose a novel deep coherence model (DCM) using a convolutional neural network architecture to capture the text coherence. The text coherence problem is investigated with a new perspective of learning sentence distributional representation and text coherence modeling simultaneously. In particular, the model captures the interactions between sentences by computing the similarities of their distributional representations. Further, it can be easily trained in an end-to-end fashion. The proposed model is evaluated on a standard Sentence Ordering task. The experimental results demonstrate its effectiveness and promise in coherence assessment showing a significant improvement over the state-of-the-art by a wide margin.

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Cited By

Li DChen TZadikian ATung AChilton L(2023)Improving Automatic Summarization for Browsing Longform Spoken DialogProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581339(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581339
Huang GShuai WGuo QDeng NLin J(2023)An Analysis Model of English Text Coherence Based on RST Dependency Relationship2023 4th International Conference on Information Science, Parallel and Distributed Systems (ISPDS)10.1109/ISPDS58840.2023.10235581(117-120)Online publication date: 14-Jul-2023
https://doi.org/10.1109/ISPDS58840.2023.10235581
Darchuk N(2022)Coreference in the poetic works of Lesia UkrainkaUkrainian Linguistics10.17721/um/52(2022).93-115(93-115)Online publication date: 2022
https://doi.org/10.17721/um/52(2022).93-115
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Index Terms

Text Coherence Analysis Based on Deep Neural Network
1. Information systems
  1. Information retrieval
    1. Document representation
      1. Content analysis and feature selection

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Published In

cover image ACM Conferences

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

November 2017

2604 pages

ISBN:9781450349185

DOI:10.1145/3132847

General Chairs:
Ee-Peng Lim
Singapore Management University, Singapore
,
Marianne Winslett
University of Illinois at Urbana-Champaign, USA, and Advanced Digital Sciences Center, Singapore
,
Program Chairs:
Mark Sanderson
RMIT, Australia
,
Ada Fu
Chinese University of Hong Kong, Hong Kong
,
Jimeng Sun
Georgia Tech, USA
,
Shane Culpepper
RMIT, Australia
,
Eric Lo
Chinese University of Hong Kong, Hong Kong
,
Joyce Ho
Emory University, USA
,
Debora Donato
Mix Tech, Inc., USA
,
Rakesh Agrawal
Data Insights Laboratories, USA
,
Yu Zheng
Microsoft Research Asia, China
,
Carlos Castillo
Qatar Computing Research Institute, Qatar
,
Aixin Sun
Nanyang Technological University, Singapore
,
Vincent S. Tseng
National Cheng Kung University, Taiwan
,
Chenliang Li
Wuhan University, China

Copyright © 2017 ACM.

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Publication History

Published: 06 November 2017

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Short-paper

Funding Sources

National Natural Science Foundation of China
the Fundamental Research Funds for the Central Universities
Zhejiang Provincial Engineering Center on Media Data Cloud Processing and Analysis

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CIKM '17

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CIKM '17: ACM Conference on Information and Knowledge Management

November 6 - 10, 2017

Singapore, Singapore

Acceptance Rates

CIKM '17 Paper Acceptance Rate 171 of 855 submissions, 20%;

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

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CIKM '25

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The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

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Cited By

Li DChen TZadikian ATung AChilton L(2023)Improving Automatic Summarization for Browsing Longform Spoken DialogProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581339(1-20)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581339
Huang GShuai WGuo QDeng NLin J(2023)An Analysis Model of English Text Coherence Based on RST Dependency Relationship2023 4th International Conference on Information Science, Parallel and Distributed Systems (ISPDS)10.1109/ISPDS58840.2023.10235581(117-120)Online publication date: 14-Jul-2023
https://doi.org/10.1109/ISPDS58840.2023.10235581
Darchuk N(2022)Coreference in the poetic works of Lesia UkrainkaUkrainian Linguistics10.17721/um/52(2022).93-115(93-115)Online publication date: 2022
https://doi.org/10.17721/um/52(2022).93-115
Duari SBhatnagar V(2022)FFCD: A Fast-and-Frugal Coherence Detection MethodIEEE Access10.1109/ACCESS.2021.313504810(85305-85314)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2021.3135048
Kramov APogorilyy S(2022)Estimation of the Local and Global Coherence of Ukrainian Texts Using Transformer-Based, LSTM, and Graph Neural NetworksICTERI 2021 Workshops10.1007/978-3-031-14841-5_33(493-509)Online publication date: 14-Sep-2022
https://doi.org/10.1007/978-3-031-14841-5_33
Telenyk SPogorilyy SKramov A(2021)Evaluation of the Coherence of Polish Texts Using Neural Network ModelsApplied Sciences10.3390/app1107321011:7(3210)Online publication date: 2-Apr-2021
https://doi.org/10.3390/app11073210
Singh MShrivastava M(2021)Fusion of Intrinsic & Extrinsic Sentential Traits for Text Coherence AssessmentProceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)10.1145/3430984.3431040(253-256)Online publication date: 2-Jan-2021
https://dl.acm.org/doi/10.1145/3430984.3431040
Li YCui BZhang Z(2021)Efficient Relational Sentence Ordering NetworkIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2021.3085738(1-1)Online publication date: 2021
https://doi.org/10.1109/TPAMI.2021.3085738
Farahnak FKosseim L(2021)Using Conditional Sentence Representation in Pointer Networks for Sentence Ordering2021 IEEE 15th International Conference on Semantic Computing (ICSC)10.1109/ICSC50631.2021.00056(288-295)Online publication date: Jan-2021
https://doi.org/10.1109/ICSC50631.2021.00056
Atri KAdlakha MGoel S(2021)A Pragmatic Approach to Web-Summarizer System2021 International Conference on Intelligent Technologies (CONIT)10.1109/CONIT51480.2021.9498320(1-5)Online publication date: 25-Jun-2021
https://doi.org/10.1109/CONIT51480.2021.9498320
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