header

Interactive Ontology Debugging: Two Query Strategies for Efficient Fault Localization

23 Pages Posted: 6 Jul 2018 Publication Status: Accepted

See all articles by Kostyantyn Shchekotykhin

Kostyantyn Shchekotykhin

Alpen-Adria-University Klagenfurt

Gerhard Friedrich

Alpen-Adria-University Klagenfurt

Philipp Fleiss

Alpen-Adria-University Klagenfurt

Patrick Rodler

Alpen-Adria-University Klagenfurt

Abstract

Effective debugging of ontologies is an important prerequisite for their broad application, especially in areas that rely on everyday users to create and maintain knowledge bases, such as the Semantic Web. In such systems ontologies capture formalized vocabularies of terms shared by its users. However in many cases users have different local views of the domain, i.e. of the context in which a given term is used. Inappropriate usage of terms together with natural complications when formulating and understanding logical descriptions may result in faulty ontologies. Recent ontology debugging approaches use diagnosis methods to identify causes of the faults. In most debugging scenarios these methods return many alternative diagnoses, thus placing the burden of fault localization on the user. This paper demonstrates how the target diagnosis can be identified by performing a sequence of observations, that is, by querying an oracle about entailments of the target ontology. To identify the best query we propose two query selection strategies: a simple "split-in-half" strategy and an entropy-based strategy. The latter allows knowledge about typical user errors to be exploited to minimize the number of queries. Our evaluation showed that the entropy-based method significantly reduces the number of required queries compared to the "split-in-half" approach. We experimented with different probability distributions of user errors and different qualities of the apriori probabilities. Our measurements demonstrated the superiority of entropy-based query selection even in cases where all fault probabilities are equal, i.e. where no information about typical user errors is available.

Keywords: ontology debugging, query selection, model-based diagnosis, description logic

Suggested Citation

Shchekotykhin, Kostyantyn and Friedrich, Gerhard and Fleiss, Philipp and Rodler, Patrick, Interactive Ontology Debugging: Two Query Strategies for Efficient Fault Localization (2012). Journal of Web Semantics First Look 12_0_7, Available at SSRN: https://ssrn.com/abstract=3198953 or http://dx.doi.org/10.2139/ssrn.3198953

Kostyantyn Shchekotykhin (Contact Author)

Alpen-Adria-University Klagenfurt ( email )

Universitätsstrasse 65-67
Klagenfurt, Corinthia A-9020
Austria

Gerhard Friedrich

Alpen-Adria-University Klagenfurt ( email )

Universitätsstrasse 65-67
Klagenfurt, Corinthia A-9020
Austria

Philipp Fleiss

Alpen-Adria-University Klagenfurt ( email )

Universitätsstrasse 65-67
Klagenfurt, Carinthia 9020
Austria

Patrick Rodler

Alpen-Adria-University Klagenfurt ( email )

Universitätsstrasse 65-67
Klagenfurt, Carinthia 9020
Austria

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Abstract Views
221
Downloads
5
PlumX Metrics