dARe – Using Argumentation to Explain Conclusions from a Controlled Natural Language Knowledge Base

Adam Wyner*, Hannes Strass

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

2 Citations (Scopus)

Abstract

We present an approach to reasoning with knowledge bases comprised of strict and defeasible rules over literals. A controlled natural language is proposed as a human/machine interface to facilitate the specification of knowledge and verbalisation of results. Techniques from formal argumentation theory are employed to justify conclusions of the approach; this aims at facilitating human acceptance of computed answers.

Original languageEnglish
Title of host publicationAdvances in Artificial Intelligence
Subtitle of host publicationFrom Theory to Practice - 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, Proceedings
EditorsSalem Benferhat, Karim Tabia, Moonis Ali
PublisherSpringer Verlag
Pages328-338
Number of pages11
Volume10351 LNCS
ISBN (Electronic)9783319600451
ISBN (Print)9783319600444
DOIs
Publication statusPublished - 2017
Event30th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, IEA/AIE 2017 - Arras, France
Duration: 27 Jun 201730 Jun 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10351 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference30th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, IEA/AIE 2017
Country/TerritoryFrance
CityArras
Period27/06/1730/06/17

Fingerprint

Dive into the research topics of 'dARe – Using Argumentation to Explain Conclusions from a Controlled Natural Language Knowledge Base'. Together they form a unique fingerprint.

Cite this