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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Rettinger, A., Lösch, U., Tresp, V., d’Amato, C., Fanizzi, N.: Mining the semantic web - statistical learning for next generation knowledge bases. Data Min. Knowl. Discov. 24, 613–662 (2012)
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P. (eds.): The Description Logic Handbook, 2nd edn. Cambridge University Press (2007)
Fanizzi, N., d’Amato, C., Esposito, F.: Induction of concepts in web ontologies through terminological decision trees. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010, Part I. LNCS, vol. 6321, pp. 442–457. Springer, Heidelberg (2010)
Blockeel, H., De Raedt, L.: Top-down induction of first-order logical decision trees. Artif. Intell. 101, 285–297 (1998)
Klir, J.: Uncertainty and Information. Wiley (2006)
Rizzo, G., d’Amato, C., Fanizzi, N., Esposito, F.: Assertion prediction with ontologies through evidence combination. In: Bobillo, F., Costa, P.C.G., d’Amato, C., Fanizzi, N., Laskey, K.B., Laskey, K.J., Lukasiewicz, T., Nickles, M., Pool, M. (eds.) URSW 2008-2010/UniDL 2010. LNCS, vol. 7123, pp. 282–299. Springer, Heidelberg (2013)
Heath, T., Bizer, C.: Linked Data: Evolving the Web into a Global Data Space. Synthesis Lectures on the Semantic Web. Morgan & Claypool Publishers (2011)
Denoeux, T.: A k-nearest neighbor classification rule based on Dempster-Shafer theory. IEEE Transactions on Systems, Man and Cybernetics 25, 804–813 (1995)
Sutton-Charani, N., Destercke, S., Denœux, T.: Classification trees based on belief functions. In: Denœux, T., Masson, M.-H. (eds.) Belief Functions: Theory & Appl. AISC, vol. 164, pp. 77–84. Springer, Heidelberg (2012)
Dubois, D., Prade, H.: On the combination of evidence in various mathematical frameworks. In: Flamm, J., Luisi, T. (eds.) Reliability Data Collection and Analysis. Eurocourses, vol. 3, pp. 213–241. Springer Netherlands (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-319-08795-5_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08794-8
Online ISBN: 978-3-319-08795-5
eBook Packages: Computer ScienceComputer Science (R0)