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  • 标题:ニューラルネットワークを用いた雑談対話からのユーザの興味推定
  • 本地全文:下载
  • 作者:稲葉 通将 ; 高橋 健一
  • 期刊名称:人工知能学会論文誌
  • 印刷版ISSN:1346-0714
  • 电子版ISSN:1346-8030
  • 出版年度:2019
  • 卷号:34
  • 期号:2
  • 页码:1-9
  • DOI:10.1527/tjsai.E-I94
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:Non-task-oriented dialogue systems are required to chat with users in accordance with their interests. In this study, we propose a neural network-based method for estimating speakers’ levels of interest from dialogues. Our model first converts given utterances into utterance vectors using a word sequence encoder with word attention. Afterward, our novel attention approach, sentence-specific sentence attention extracts useful information for estimating the level of interest. Additionally, we introduce a new pre-training method for our model. Experimental results indicated that it was most effective to use topic-specific sentence attention and proposed pre-training in combination.
  • 关键词:Interest Estimation;Personalization;Chat Dialogue;Dialogue System
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