Bayesian model selection in statistical construction of justification

Kido, Hiroyuki ORCID: https://orcid.org/0000-0002-7622-4428 2018. Bayesian model selection in statistical construction of justification. Presented at: Sixteenth International Conference on Principles of Knowledge Representation and Reasoning, Tempe, Arizona (USA), 27 October - 2 November 2018. Published in: Thielscher, Michael, Toni, Francesca and Wolter, Frank eds. Principles of Knowledge Representation and Reasoning: Proceedings of the Sixteenth International Conference (KR2018). Palo Alto, California: Association for the Advancement of Artificial Intelligence, pp. 647-648.

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Abstract

Argumentation mining involves identification of an attack relation between natural language sentences. Bayesian inference characterizing argument-based reasoning addresses this issue by calculating the posterior distribution over attack relations given acceptability statuses of arguments. This paper discusses the use of Bayesian model selection where graph-theoretic properties impose restrictions on the graphic structure of attack relations.

Item Type:	Conference or Workshop Item - published (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	Association for the Advancement of Artificial Intelligence
ISBN:	978-1-57735-803-9
ISSN:	2334-1025
Date of First Compliant Deposit:	10 December 2019
Date of Acceptance:	11 July 2018
Last Modified:	18 Mar 2026 11:41
URI:	https://orca.cardiff.ac.uk/id/eprint/127445

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