Parsing graphical summaries from argumentative dialogues

Clayton, J., Damonte, M. and Gaizauskas, R. orcid.org/0000-0002-3356-5126 (2024) Parsing graphical summaries from argumentative dialogues. In: Reed, C., Thimm, M. and Rienstra, T., (eds.) Computational Models of Argument: Proceedings of COMMA 2024. The 10th International Conference on Computational Models of Argument, 18-20 Sep 2024, Hagen, Germany. Frontiers in Artificial Intelligence and Applications, 388 . IOS Press , pp. 37-48. ISBN 9781643685342

Abstract

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Reed, C.
  • Thimm, M.
  • Rienstra, T.
Copyright, Publisher and Additional Information:

© 2024 The Authors. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0 / https://creativecommons.org/licenses/by-nc/4.0/)

Keywords: Argument Mining; Summarisation; Stance Detection; TANL
Dates:
  • Published: 2024
  • Published (online): 27 August 2024
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield)
Funding Information:
Funder
Grant number
ENGINEERING AND PHYSICAL SCIENCE RESEARCH COUNCIL
EP/S023062/1
COMMERCIAL MASTER ACCOUNT
UNSPECIFIED
Depositing User: Symplectic Sheffield
Date Deposited: 18 Feb 2025 15:23
Last Modified: 18 Feb 2025 15:24
Status: Published
Publisher: IOS Press
Series Name: Frontiers in Artificial Intelligence and Applications
Refereed: Yes
Identification Number: 10.3233/FAIA240308
Open Archives Initiative ID (OAI ID):

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