Grant, J;
Hunter, A;
(2017)
Analysing inconsistent information using distance-based measures.
International Journal of Approximate Reasoning
, 89
pp. 3-26.
10.1016/j.ijar.2016.04.004.
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Abstract
There have been a number of proposals for measuring inconsistency in a knowledgebase (i.e. a set of logical formulae). These include measures that consider the minimally inconsistent subsets of the knowledgebase, and measures that consider the paraconsistent models (3 or 4 valued models) of the knowledgebase. In this paper, we present a new approach that considers the amount by which each formula has to be weakened in order for the knowledgebase to be consistent. This approach is based on ideas of knowledge merging by Konienczny and Pino-Perez. We show that this approach gives us measures that are different from existing measures, that have desirable properties, and that can take the significance of inconsistencies into account. The latter is useful when we want to differentiate between inconsistencies that have minor significance from inconsistencies that have major significance. We also show how our measures are potentially useful in applications such as evaluating violations of integrity constraints in databases and for deciding how to act on inconsistency.
| Type: | Article |
|---|---|
| Title: | Analysing inconsistent information using distance-based measures |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ijar.2016.04.004 |
| Publisher version: | http://dx.doi.org/10.1016/j.ijar.2016.04.004 |
| Language: | English |
| Additional information: | Copyright © 2016. This manuscript version is published under a Creative Commons Attribution Non-commercial Non-derivative 4.0 International licence (CC BY-NC-ND 4.0). This licence allows you to share, copy, distribute and transmit the work for personal and non-commercial use providing author and publisher attribution is clearly stated. Further details about CC BY licences are available at http://creativecommons.org/licenses/by/4.0. |
| Keywords: | Inconsistency measurement; Inconsistency analysis; Inconsistency management; Inconsistency tolerance; Propositional logic; Distance measures |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1492987 |
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