Chatbot with a Discourse Structure-Driven Dialogue Management

Boris Galitsky, Dmitry Ilvovsky


Abstract
We build a chat bot with iterative content exploration that leads a user through a personalized knowledge acquisition session. The chat bot is designed as an automated customer support or product recommendation agent assisting a user in learning product features, product usability, suitability, troubleshooting and other related tasks. To control the user navigation through content, we extend the notion of a linguistic discourse tree (DT) towards a set of documents with multiple sections covering a topic. For a given paragraph, a DT is built by DT parsers. We then combine DTs for the paragraphs of documents to form what we call extended DT, which is a basis for interactive content exploration facilitated by the chat bot. To provide cohesive answers, we use a measure of rhetoric agreement between a question and an answer by tree kernel learning of their DTs.
Anthology ID:
E17-3022
Volume:
Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics
Month:
April
Year:
2017
Address:
Valencia, Spain
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
87–90
Language:
URL:
https://aclanthology.org/E17-3022
DOI:
Bibkey:
Cite (ACL):
Boris Galitsky and Dmitry Ilvovsky. 2017. Chatbot with a Discourse Structure-Driven Dialogue Management. In Proceedings of the Software Demonstrations of the 15th Conference of the European Chapter of the Association for Computational Linguistics, pages 87–90, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Chatbot with a Discourse Structure-Driven Dialogue Management (Galitsky & Ilvovsky, EACL 2017)
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PDF:
https://preview.aclanthology.org/author-url/E17-3022.pdf