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Personalized Response Generation via Domain adaptation

Published: 07 August 2017 Publication History

Abstract

In this paper, we propose a novel personalized response generation model via domain adaptation (PRG-DM). First, we learn the human responding style from large general data (without user-specific information). Second, we fine tune the model on a small size of personalized data to generate personalized responses with a dual learning mechanism. Moreover, we propose three new rewards to characterize good conversations that are personalized, informative and grammatical. We employ the policy gradient method to generate highly rewarded responses. Experimental results show that our model can generate better personalized responses for different users.

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  • (2024)Error Correction and Adaptation in Conversational AI: A Review of Techniques and Applications in ChatbotsAI10.3390/ai50200415:2(803-841)Online publication date: 4-Jun-2024
  • (2023)A Stack-Propagation Framework for Low-Resource Personalized Dialogue GenerationACM Transactions on Information Systems10.1145/356338941:3(1-36)Online publication date: 4-Apr-2023
  • (2023)A Background Knowledge Revising and Incorporating Dialogue ModelIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.312312834:8(3874-3884)Online publication date: Aug-2023
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cover image ACM Conferences
SIGIR '17: Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval
August 2017
1476 pages
ISBN:9781450350228
DOI:10.1145/3077136
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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Publication History

Published: 07 August 2017

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Author Tags

  1. domain adaptation
  2. reinforcement learning
  3. response generation

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SIGIR '17
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SIGIR '17 Paper Acceptance Rate 78 of 362 submissions, 22%;
Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

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  • (2024)Error Correction and Adaptation in Conversational AI: A Review of Techniques and Applications in ChatbotsAI10.3390/ai50200415:2(803-841)Online publication date: 4-Jun-2024
  • (2023)A Stack-Propagation Framework for Low-Resource Personalized Dialogue GenerationACM Transactions on Information Systems10.1145/356338941:3(1-36)Online publication date: 4-Apr-2023
  • (2023)A Background Knowledge Revising and Incorporating Dialogue ModelIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.312312834:8(3874-3884)Online publication date: Aug-2023
  • (2023)Building Intelligent Chatbots: Tools, Technologies, and Approaches2023 3rd International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET)10.1109/IRASET57153.2023.10153005(1-12)Online publication date: 18-May-2023
  • (2022)Personalizing Task-oriented Dialog Systems via Zero-shot Generalizable Reward FunctionProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557417(1787-1797)Online publication date: 17-Oct-2022
  • (2021)A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User ProfilesProceedings of the Web Conference 202110.1145/3442381.3449843(1552-1561)Online publication date: 19-Apr-2021
  • (2021)Conditional Text Generation for Harmonious Human-Machine InteractionACM Transactions on Intelligent Systems and Technology10.1145/343981612:2(1-50)Online publication date: 26-Feb-2021
  • (2021)Multitask Learning and Reinforcement Learning for Personalized Dialog Generation: An Empirical StudyIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2020.297503532:1(49-62)Online publication date: Jan-2021
  • (2021)Neural Attentive Network for Cross-Domain Aspect-Level Sentiment ClassificationIEEE Transactions on Affective Computing10.1109/TAFFC.2019.289709312:3(761-775)Online publication date: 1-Jul-2021
  • (2021)Automatic text summary generation method based on hybrid model DNM2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC52423.2021.9659022(637-642)Online publication date: 17-Oct-2021
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