Measuring Disagreement among Knowledge Bases

EasyChair Preprint no. 218

14 pagesDate: June 1, 2018

Abstract

When combining beliefs from different sources,
often not only new knowledge but also conflicts arise.
In this paper, we investigate how we can measure the disagreement
among sources. We start our investigation with disagreement measures
that can be induced from inconsistency measures in an automated way.
After discussing some problems with this approach,
we propose a new measure that is inspired by the $\eta$-inconsistency measure.
Roughly speaking, it measures how well we can satisfy all sources simultaneously.
We show that the new measure satisfies desirable properties,
scales well with respect to the number of sources and illustrate its applicability
in inconsistency-tolerant reasoning.

Keyphrases: belief merging, disagreement measure, Inconsistency measures, Inconsistency-tolerant reasoning