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Neural Personalized Response Generation as Domain Adaptation ...
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Abstract:
In this paper, we focus on the personalized response generation for conversational systems. Based on the sequence to sequence learning, especially the encoder-decoder framework, we propose a two-phase approach, namely initialization then adaptation, to model the responding style of human and then generate personalized responses. For evaluation, we propose a novel human aided method to evaluate the performance of the personalized response generation models by online real-time conversation and offline human judgement. Moreover, the lexical divergence of the responses generated by the 5 personalized models indicates that the proposed two-phase approach achieves good results on modeling the responding style of human and generating personalized responses for the conversational systems. ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1701.02073 https://arxiv.org/abs/1701.02073
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Exploiting Multi-typed Treebanks for Parsing with Deep Multi-task Learning ...
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Additional file 1: of Prediction of the next highly pathogenic avian influenza pandemic that can cause illness in humans ...
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Additional file 1: of Prediction of the next highly pathogenic avian influenza pandemic that can cause illness in humans ...
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Modeling Leadership Behavior of Players in Virtual Worlds
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In: Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment; Vol. 11 No. 1 (2015): Eleventh Artificial Intelligence and Interactive Digital Entertainment Conference ; 2334-0924 ; 2326-909X (2015)
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Effective LSTMs for Target-Dependent Sentiment Classification ...
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Question Popularity Analysis and Prediction in Community Question Answering Services
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32 |
Phrasal Paraphrase Based Question Reformulation for Archived Question Retrieval
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33 |
Correction: Phrasal Paraphrase Based Question Reformulation for Archived Question Retrieval
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