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    <abstract>We address the problem of acquiring the ontological categories of unknown terms through implicit confirmation in dialogues. We develop an approach that makes implicit confirmation requests with an unknown term’s predicted category. Our approach does not degrade user experience with repetitive explicit confirmations, but the system has difficulty determining if information in the confirmation request can be correctly acquired. To overcome this challenge, we propose a method for determining whether or not the predicted category is correct, which is included in an implicit confirmation request. Our method exploits multiple user responses to implicit confirmation requests containing the same ontological category. Experimental results revealed that the proposed method exhibited a higher precision rate for determining the correctly predicted categories than when only single user responses were considered.</abstract>
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%0 Conference Proceedings
%T Lexical Acquisition through Implicit Confirmations over Multiple Dialogues
%A Ono, Kohei
%A Takeda, Ryu
%A Nichols, Eric
%A Nakano, Mikio
%A Komatani, Kazunori
%Y Jokinen, Kristiina
%Y Stede, Manfred
%Y DeVault, David
%Y Louis, Annie
%S Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
%D 2017
%8 August
%I Association for Computational Linguistics
%C Saarbrücken, Germany
%F ono-etal-2017-lexical
%X We address the problem of acquiring the ontological categories of unknown terms through implicit confirmation in dialogues. We develop an approach that makes implicit confirmation requests with an unknown term’s predicted category. Our approach does not degrade user experience with repetitive explicit confirmations, but the system has difficulty determining if information in the confirmation request can be correctly acquired. To overcome this challenge, we propose a method for determining whether or not the predicted category is correct, which is included in an implicit confirmation request. Our method exploits multiple user responses to implicit confirmation requests containing the same ontological category. Experimental results revealed that the proposed method exhibited a higher precision rate for determining the correctly predicted categories than when only single user responses were considered.
%R 10.18653/v1/W17-5507
%U https://aclanthology.org/W17-5507
%U https://doi.org/10.18653/v1/W17-5507
%P 50-59

Markdown (Informal)

[Lexical Acquisition through Implicit Confirmations over Multiple Dialogues](https://aclanthology.org/W17-5507) (Ono et al., SIGDIAL 2017)

• Lexical Acquisition through Implicit Confirmations over Multiple Dialogues (Ono et al., SIGDIAL 2017)

ACL

• Kohei Ono, Ryu Takeda, Eric Nichols, Mikio Nakano, and Kazunori Komatani. 2017. Lexical Acquisition through Implicit Confirmations over Multiple Dialogues. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, pages 50–59, Saarbrücken, Germany. Association for Computational Linguistics.