research-article

Chat More: Deepening and Widening the Chatting Topic via A Deep Model

Authors:

Liqiang NieAuthors Info & Claims

SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval

Pages 255 - 264

https://doi.org/10.1145/3209978.3210061

Published: 27 June 2018 Publication History

Abstract

The past decade has witnessed the boom of human-machine interactions, particularly via dialog systems. In this paper, we study the task of response generation in open-domain multi-turn dialog systems. Many research efforts have been dedicated to building intelligent dialog systems, yet few shed light on deepening or widening the chatting topics in a conversational session, which would attract users to talk more. To this end, this paper presents a novel deep scheme consisting of three channels, namely global, wide, and deep ones. The global channel encodes the complete historical information within the given context, the wide one employs an attention-based recurrent neural network model to predict the keywords that may not appear in the historical context, and the deep one trains a Multi-layer Perceptron model to select some keywords for an in-depth discussion. Thereafter, our scheme integrates the outputs of these three channels to generate desired responses. To justify our model, we conducted extensive experiments to compare our model with several state-of-the-art baselines on two datasets: one is constructed by ourselves and the other is a public benchmark dataset. Experimental results demonstrate that our model yields promising performance by widening or deepening the topics of interest.

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Cited By

Wang JLin DLi W(2024)Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive DialogueACM Transactions on Information Systems10.1145/365259842:5(1-27)Online publication date: 27-Apr-2024
https://dl.acm.org/doi/10.1145/3652598
Okada TShimakawa HKuwabara K(2024)Smoothing Conversation Using Dialogue Agents Accompanied by Advisory Agent Inside2024 9th International Conference on Frontiers of Signal Processing (ICFSP)10.1109/ICFSP62546.2024.10785402(147-152)Online publication date: 12-Sep-2024
https://doi.org/10.1109/ICFSP62546.2024.10785402
Zhou YZhi CXu FCui WWang HQin AChen XWang YHuang X(2023)Keyword-Aware Transformers Network for Chinese Open-Domain Conversation GenerationElectronics10.3390/electronics1205122812:5(1228)Online publication date: 4-Mar-2023
https://doi.org/10.3390/electronics12051228
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Index Terms

Chat More: Deepening and Widening the Chatting Topic via A Deep Model
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Discourse, dialogue and pragmatics
      2. Natural language generation

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cover image ACM Conferences

SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval

June 2018

1509 pages

ISBN:9781450356572

DOI:10.1145/3209978

General Chairs:
Kevyn Collins-Thompson
University of Michigan, United States
,
Qiaozhu Mei
University of Michigan, United States
,
Program Chairs:
Brian Davison
Lehigh University, United States
,
Yiqun Liu
Tsinghua University, China
,
Emine Yilmaz
University College London, United Kingdom

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Publication History

Published: 27 June 2018

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National Natural Science Foundation of China
the National Basic Research Program of China (973 Program)
the Project of Thousand Youth Talents 2016

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SIGIR '18

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SIGIR

SIGIR '18: The 41st International ACM SIGIR conference on research and development in Information Retrieval

July 8 - 12, 2018

MI, Ann Arbor, USA

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SIGIR '18 Paper Acceptance Rate 86 of 409 submissions, 21%;

Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Wang JLin DLi W(2024)Target-constrained Bidirectional Planning for Generation of Target-oriented Proactive DialogueACM Transactions on Information Systems10.1145/365259842:5(1-27)Online publication date: 27-Apr-2024
https://dl.acm.org/doi/10.1145/3652598
Okada TShimakawa HKuwabara K(2024)Smoothing Conversation Using Dialogue Agents Accompanied by Advisory Agent Inside2024 9th International Conference on Frontiers of Signal Processing (ICFSP)10.1109/ICFSP62546.2024.10785402(147-152)Online publication date: 12-Sep-2024
https://doi.org/10.1109/ICFSP62546.2024.10785402
Zhou YZhi CXu FCui WWang HQin AChen XWang YHuang X(2023)Keyword-Aware Transformers Network for Chinese Open-Domain Conversation GenerationElectronics10.3390/electronics1205122812:5(1228)Online publication date: 4-Mar-2023
https://doi.org/10.3390/electronics12051228
Ling YCai FLiu JChen Hde Rijke M(2023)Keep and Select: Improving Hierarchical Context Modeling for Multi-Turn Response GenerationIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.311270034:7(3636-3649)Online publication date: Jul-2023
https://doi.org/10.1109/TNNLS.2021.3112700
Yang RMa ZWang CDu B(2022)Enhancing Integrity Modeling for Emotional Conversation GenerationIEEE Transactions on Cognitive and Developmental Systems10.1109/TCDS.2021.309844414:3(1170-1178)Online publication date: Sep-2022
https://doi.org/10.1109/TCDS.2021.3098444
Wołk KWołk AWnuk DGrześ TSkubis I(2022)Survey on dialogue systems including slavic languagesNeurocomputing10.1016/j.neucom.2021.11.076477:C(62-84)Online publication date: 7-Mar-2022
https://dl.acm.org/doi/10.1016/j.neucom.2021.11.076
Ling YLiang ZWang TCai FChen H(2022)Hard-style Selective Context Utilization for dialogue generation based on what user just saidKnowledge-Based Systems10.1016/j.knosys.2022.109873257(109873)Online publication date: Dec-2022
https://doi.org/10.1016/j.knosys.2022.109873
Fu TGao SZhao XWen JYan R(2022)Learning towards conversational AI: A surveyAI Open10.1016/j.aiopen.2022.02.0013(14-28)Online publication date: 2022
https://doi.org/10.1016/j.aiopen.2022.02.001
Ling YLiang ZWang TCai FChen H(2022)Sequential or jumping: context-adaptive response generation for open-domain dialogue systemsApplied Intelligence10.1007/s10489-022-04067-153:9(11251-11266)Online publication date: 2-Sep-2022
https://doi.org/10.1007/s10489-022-04067-1
Coppola RArdito L(2021)Quality Assessment Methods for Textual Conversational Interfaces: A Multivocal Literature ReviewInformation10.3390/info1211043712:11(437)Online publication date: 21-Oct-2021
https://doi.org/10.3390/info12110437
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