Distance-based Measures of Inconsistency and Incoherency for Description Logics

Yue Ma (1) , Pascal Hitzler (2)

1 LIPN - Laboratoire d'Informatique de Paris-Nord
2 Kno.e.sis Center, Wright State University, Dayton, OH,USA

Inconsistency and incoherency are two sorts of erroneous information in a DL ontology which have been widely discussed in ontology-based applications. For example, they have been used to detect modeling errors during ontology construction. To provide more informative metrics which can tell the differences between inconsistent ontologies and between incoherent terminologies, there has been some work on measuring inconsistency of an ontology and on measuring incoherency of a terminology. However, most of them merely focus either on measuring inconsistency or on measuring incoherency and no clear ideas of how to extend them to allow for the other. In this paper, we propose a novel approach to measure DL ontologies, named distance-based measures. It has the merits that both inconsistency and incoherency can be measured in a unified framework. Moreover, only classical DL interpretations are used such that there is no restriction on the DL languages used.

Domaines: Intelligence artificielle [cs.AI]

Yue Ma, Pascal Hitzler. Distance-based Measures of Inconsistency and Incoherency for Description Logics. The 23rd International Workshop on Description Logics (DL 2010), Oct 2010, Canada. pp.475-485. ⟨hal-00528912⟩