@inproceedings{galitsky-ilvovsky-2017-chat,
title = "On a Chat Bot Finding Answers with Optimal Rhetoric Representation",
author = "Galitsky, Boris and
Ilvovsky, Dmitry",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing, {RANLP} 2017",
month = sep,
year = "2017",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://doi.org/10.26615/978-954-452-049-6_035",
doi = "10.26615/978-954-452-049-6_035",
pages = "253--259",
abstract = "We demo a chat bot with the focus on complex, multi-sentence questions that enforce what we call rhetoric agreement of answers with questions. Chat bot finds answers which are not only relevant by topic but also match the question by style, argumentation patterns, communication means, experience level and other attributes. The system achieves rhetoric agreement by learning pairs of discourse trees (DTs) for question (Q) and answer (A). We build a library of best answer DTs for most types of complex questions. To better recognize a valid rhetoric agreement between Q and A, DTs are extended with the labels for communicative actions. An algorithm for finding the best DT for an A, given a Q, is evaluated.",
}
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%0 Conference Proceedings
%T On a Chat Bot Finding Answers with Optimal Rhetoric Representation
%A Galitsky, Boris
%A Ilvovsky, Dmitry
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
%D 2017
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F galitsky-ilvovsky-2017-chat
%X We demo a chat bot with the focus on complex, multi-sentence questions that enforce what we call rhetoric agreement of answers with questions. Chat bot finds answers which are not only relevant by topic but also match the question by style, argumentation patterns, communication means, experience level and other attributes. The system achieves rhetoric agreement by learning pairs of discourse trees (DTs) for question (Q) and answer (A). We build a library of best answer DTs for most types of complex questions. To better recognize a valid rhetoric agreement between Q and A, DTs are extended with the labels for communicative actions. An algorithm for finding the best DT for an A, given a Q, is evaluated.
%R 10.26615/978-954-452-049-6_035
%U https://doi.org/10.26615/978-954-452-049-6_035
%P 253-259
Markdown (Informal)
[On a Chat Bot Finding Answers with Optimal Rhetoric Representation](https://doi.org/10.26615/978-954-452-049-6_035) (Galitsky & Ilvovsky, RANLP 2017)
ACL