Syntactic Filtering and Content-based Retrieval of Twitter Sentences for the Generation of System Utterances in Dialogue Systems

نویسندگان

  • Ryuichiro Higashinaka
  • Nozomi Kobayashi
  • Toru Hirano
  • Chiaki Miyazaki
  • Toyomi Meguro
  • Toshiro Makino
  • Yoshihiro Matsuo
چکیده

Sentences extracted from Twitter have been seen as a valuable resource for response generation in dialogue systems. However, selecting appropriate ones is difficult due to their noise. This paper proposes tackling such noise by syntactic filtering and content-based retrieval. Syntactic filtering ascertains the valid sentence structure as system utterances, and content-based retrieval ascertains that the content has the relevant information related to user utterances. Experimental results show that our proposed method can appropriately select high-quality Twitter sentences, significantly outperforming the baseline.

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تاریخ انتشار 2013