Abstract
An approach to improve an RCC-derived geospatial approximation is presented which makes use of concept inclusion axioms in OWL. The algorithm used to control the approximation combines hypothesis testing with consistency checking provided by a knowledge representation system based on description logics. Propositions about the consistency of the refined ABox w.r.t. the associated TBox when compared to baseline ABox and TBox are made. Formal proves of the divergent consistency results when checking either of both are provided. The application of the approach to a geospatial setting results in a roughly tenfold improved approximation when using the refined ABox and TBox. Ways to further improve the approximation and to automate the detection of falsely calculated relations are discussed. © 2008 Springer Berlin Heidelberg.
Author supplied keywords
Cite
CITATION STYLE
Grütter, R., Scharrenbach, T., & Bauer-Messmer, B. (2008). Improving an RCC-derived geospatial approximation by OWL axioms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5318 LNCS, pp. 293–306). Springer Verlag. https://doi.org/10.1007/978-3-540-88564-1_19
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
