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Interactive Ontology Revision

21 Pages Posted: 6 Jul 2018 Publication Status: Accepted

See all articles by Nadeschda Nikitina

Nadeschda Nikitina

Karlsruhe Institute of Technology - Institute AIFB

Sebastian Rudolph

Karlsruhe Institute of Technology - Institute AIFB

Birte Glimm

University of Ulm - Institute of Artificial Intelligence

Abstract

When ontological knowledge is acquired automatically, quality control is essential. We consider the tightest possible approach - an exhaustive manual inspection of the acquired data. By using automated reasoning, this process can be partially automatized: after each expert decision, axioms that are entailed by the already confirmed statements are automatically approved, whereas axioms that would lead to an inconsistency are declined. Starting from this consideration, this paper provides theoretical foundations, heuristics, optimization strategies and comprehensive experimental results for our approach to efficient reasoning-supported interactive ontology revision. We introduce and elaborate on the notions of revision states and revision closure as formal foundations of our method. Additionally, we propose a notion of axiom impact which is used to determine a beneficial order of axiom evaluation in order to further increase the effectiveness of ontology revision. The initial notion of impact is then further refined to take different validity ratios - the proportion of valid statements within a dataset - into account. Since the validity ratio is generally not known a priori - we show how one can work with an estimate that is continuously improved over the course of the inspection process. Finally, we develop the notion of decision spaces, which are structures for calculating and updating the revision closure and axiom impact. We optimize the computation performance further by employing partitioning techniques and provide an implementation supporting these optimizations as well as featuring a user front-end. Our evaluation shows that our ranking functions almost achieve the maximum possible automatization and that the computation time needed for each reasoning-based, automatic decision takes less than one second on average for our test dataset of over 25,000 statements.

Keywords: Ontologies, Knowledge Representation, Automated Reasoning, Quality Assurance, OWL

Suggested Citation

Nikitina, Nadeschda and Rudolph, Sebastian and Glimm, Birte, Interactive Ontology Revision (2012). Journal of Web Semantics First Look 12_0_9, Available at SSRN: https://ssrn.com/abstract=3198955 or http://dx.doi.org/10.2139/ssrn.3198955

Nadeschda Nikitina (Contact Author)

Karlsruhe Institute of Technology - Institute AIFB ( email )

Building 05.20 KIT-Campus South
Karlsruhe, D-76128
Germany

Sebastian Rudolph

Karlsruhe Institute of Technology - Institute AIFB ( email )

Building 05.20 KIT-Campus South
Karlsruhe, D-76128
Germany

Birte Glimm

University of Ulm - Institute of Artificial Intelligence ( email )

Albert-Einstein-Alee 11
Ulm, Baden-W├╝rttemberg D-89081
Germany

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