Abstract
We propose a method that combines terminological decision trees and the Dempster-Shafer Theory, to support tasks like ontology completion. The goal is to build a predictive model that can cope with the epistemological uncertainty due to the Open World Assumption when reasoning with Web ontologies. With such models not only one can predict new (non derivable) assertions for completing the ontology but by assessing the quality of the induced axioms.
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Rizzo, G., d’Amato, C., Fanizzi, N., Esposito, F. (2014). Towards Evidence-Based Terminological Decision Trees. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2014. Communications in Computer and Information Science, vol 442. Springer, Cham. https://doi.org/10.1007/978-3-319-08795-5_5
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DOI: https://doi.org/10.1007/978-3-319-08795-5_5
Publisher Name: Springer, Cham
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