How to Decrease and Resolve Inconsistency of a Knowledge Base?

Dragan Doder, Srdjan Vesic

Abstract

This paper studies different techniques for measuring and decreasing inconsistency of a knowledge base. We define an operation that allows to decrease inconsistency of a knowledge base while losing a minimal amount of information. We also propose two different ways to compare knowledge bases. The first is a partial order that we define on the set of knowledge bases. We study this relation and identify its link with a particular class of inconsistency measures. We also study the links between the partial order we introduce and information measures. The second way we propose to compare knowledge bases is to define a class of metrics that give us a distance between knowledge bases. They are based on symmetric set difference of models of pairs of formulae from the two sets in question.

References

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Paper Citation


in Harvard Style

Doder D. and Vesic S. (2015). How to Decrease and Resolve Inconsistency of a Knowledge Base? . In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-074-1, pages 27-37. DOI: 10.5220/0005176500270037


in Bibtex Style

@conference{icaart15,
author={Dragan Doder and Srdjan Vesic},
title={How to Decrease and Resolve Inconsistency of a Knowledge Base?},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2015},
pages={27-37},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005176500270037},
isbn={978-989-758-074-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - How to Decrease and Resolve Inconsistency of a Knowledge Base?
SN - 978-989-758-074-1
AU - Doder D.
AU - Vesic S.
PY - 2015
SP - 27
EP - 37
DO - 10.5220/0005176500270037