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  • 标题:パーソナライズ可能な対話システムのためのユーザ情報抽出
  • 本地全文:下载
  • 作者:平野 徹 ; 小林 のぞみ ; 東中 竜一郎
  • 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:2016
  • 卷号:31
  • 期号:1
  • 页码:DSF-B_1-10
  • DOI:10.1527/tjsai.DSF-512
  • 出版社:The Japanese Society for Artificial Intelligence
  • 摘要:We propose a method to extract user information in a structured form for personalized dialogue systems. Assuming that user information can be represented as a quadruple , we focus on solving problems in extracting predicate argument structures from question-answer pairs in which arguments and predicates are frequently omitted, and in estimating attribute categories related to user behavior which a method using only content words cannot distinguish. Experimental results show that the proposed method significantly outperformed baseline methods and was able to extract user information with 81.2% precision and 58.1% recall.
  • 关键词:personalized dialogue systems;user information extraction;predicate-argument structure analysis
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