Abstract
Fuzzy Description Logics (DLs) are logics that allow to deal with vague structured knowledge. Although a relatively important amount of work has been carried out in the last years concerning the use of fuzzy DLs as ontology languages, the problem of automatically managing fuzzy ontologies has received no attention so far. We report here our preliminary investigation on this issue by describing a method for inducing inclusion axioms in a fuzzy DL-Lite like DL.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2003)
Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Data complexity of query answering in description logics. In: Proc. of the 10th Int. Conf. on Principles of Knowledge Representation and Reasoning, pp. 260–270 (2006)
Drobics, M., Bodenhofer, U., Klement, E.-P.: FS-FOIL: an inductive learning method for extracting interpretable fuzzy descriptions. Int. J. Approximate Reasoning 32(2-3), 131–152 (2003)
Hellmann, S., Lehmann, J., Auer, S.: Learning of OWL Class Descriptions on Very Large Knowledge Bases. Int. J. on Semantic Web and Information Systems 5(2), 25–48 (2009)
Horváth, T., Vojtás, P.: Induction of fuzzy and annotated logic programs. In: Muggleton, S.H., Otero, R., Tamaddoni-Nezhad, A. (eds.) ILP 2006. LNCS (LNAI), vol. 4455, pp. 260–274. Springer, Heidelberg (2007)
Klir, G.J., Yuan, B.: Fuzzy sets and fuzzy logic: theory and applications. Prentice-Hall, Inc., Upper Saddle River (1995)
Lukasiewicz, T., Straccia, U.: Top-k retrieval in description logic programs under vagueness for the semantic web. In: Prade, H., Subrahmanian, V.S. (eds.) SUM 2007. LNCS (LNAI), vol. 4772, pp. 16–30. Springer, Heidelberg (2007)
Lukasiewicz, T., Straccia, U.: Managing uncertainty and vagueness in description logics for the semantic web. Journal of Web Semantics 6, 291–308 (2008)
Nienhuys-Cheng, S.-H., de Wolf, R.: Foundations of Inductive Logic Programming. LNCS(LNAI), vol. 1228. Springer, Heidelberg (1997)
Quinlan, J.R.: Learning logical definitions from relations. Machine Learning 5, 239–266 (1990)
Serrurier, M., Prade, H.: Improving expressivity of inductive logic programming by learning different kinds of fuzzy rules. Soft Computing 11(5), 459–466 (2007)
Shibata, D., Inuzuka, N., Kato, S., Matsui, T., Itoh, H.: An induction algorithm based on fuzzy logic programming. In: Zhong, N., Zhou, L. (eds.) PAKDD 1999. LNCS (LNAI), vol. 1574, pp. 268–274. Springer, Heidelberg (1999)
Straccia, U.: Reasoning within fuzzy description logics. Journal of Artificial Intelligence Research 14, 137–166 (2001)
Straccia, U.: SoftFacts: a top-k retrieval engine for a tractable description logic accessing relational databases. Technical report (2009)
Straccia, U.: SoftFacts: A top-k retrieval engine for ontology mediated access to relational databases. In: Proc. of the 2010 IEEE Int. Conf. on Systems, Man and Cybernetics, pp. 4115–4122. IEEE Press, Los Alamitos (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lisi, F.A., Straccia, U. (2011). Towards Learning Fuzzy DL Inclusion Axioms. In: Fanelli, A.M., Pedrycz, W., Petrosino, A. (eds) Fuzzy Logic and Applications. WILF 2011. Lecture Notes in Computer Science(), vol 6857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23713-3_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-23713-3_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23712-6
Online ISBN: 978-3-642-23713-3
eBook Packages: Computer ScienceComputer Science (R0)