Towards Large-Scale Inconsistency Measurement

Abstract

Abstract. We investigate the problem of inconsistency measurement on large knowledge bases by considering stream-based inconsistency measurement, i. e., we investigate inconsistency measures that cannot consider a knowledge base as a whole but process it within a stream. For that, we present, first, a novel inconsistency measure that is apt to be applied to the streaming case and, second, stream-based approximations for the new and some existing inconsistency measures. We conduct an extensive empirical analysis on the behavior of these inconsistency measures on large knowledge bases, in terms of runtime, accuracy, and scalability. We conclude that for two of these measures, the approximation of the new inconsistency measure and an approximation of the contension inconsistency measure, large-scale inconsistency measurement is feasible.

Measuring Disagreement in Argumentation Graphs

“…Motivated by important applications like software specifications, quantifying inconsistency in a KB has become a hot topic the last six years (e.g. [6][7][8][9][10][11]). Since the number of applications of argumentation grows steadily, it is important that the approach has its own tools for answering various needs of the applications including measuring inconsistency.…”