Abstract
In order to overcome human and time resource problems in the task of ontology design, we propose to combine the LExO approach to learning expressive ontology axioms from textual definitions with Relational Exploration – a technique based on the well-known attribute exploration algorithm from FCA which is used to interactively clarify underspecified logical dependencies. By forcing particular modeling decisions the exploration of classes and class extension relationships guarantees completeness with respect to a certain logical fragment and increases the overall quality of the ontology. Providing an implementation as well as an example, we demonstrate how ontology learning and exploration complement each other in a synergetic way.
This work has been supported by the European Commission under contract IST-2006-027595 NeOn, and by the Deutsche Forschungsgemeinschaft (DFG) under the ReaSem project.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
McGuinness, D.L., van Harmelen, F.: OWL Web Ontology Language Overview (2004), CTAN: http://www.w3.org/TR/2004/REC-owl-features-20040210/
Hearst, M.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the 14th International Conference on Computational Linguistics, pp. 539–545 (1992)
Harris, Z.S.: Word. Distributional Structure 10, 146–162 (1954)
Velardi, P., et al.: Evaluation of ontolearn, a methodology for automatic population of domain ontologies. In: Ontology Learning from Text: Methods, Applications and Evaluation, IOS Press, Amsterdam (2005)
Buitelaar, P., Olejnik, D., Sintek, M.: OntoLT: A Protégé plug-in for ontology extraction from text. In: Fensel, D., Sycara, K.P., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, Springer, Heidelberg (2003)
Cimiano, P., Völker, J.: Text2Onto - a framework for ontology learning and data-driven change discovery. In: Proc. of the 10th International Conference on Applications of Natural Language to Information Systems, pp. 227–238. Springer, Heidelberg (2005)
Völker, J., Hitzler, P., Cimiano, P.: Acquisition of OWL DL axioms from lexical resources. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, Springer, Heidelberg (2007)
Fanizzi, N., et al.: Concept formation in expressive description logics. In: Boulicaut, J.-F., et al. (eds.) ECML 2004. LNCS (LNAI), vol. 3201, Springer, Heidelberg (2004)
Cohen, W.W., Hirsh, H.: Learning the classic description logic: Theoretical and experimental results. In: Doyle, J., Sandewall, E., Torasso, P. (eds.) Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning (KR 1994), Bonn, Germany, May 24-27, 1994, pp. 121–133. Morgan Kaufmann, San Francisco (1994)
Rudolph, S.: Relational Exploration - Combining Description Logics and Formal Concept Analysis for Knowledge Specification. Universitätsverlag Karlsruhe, Dissertation (2006)
Stumme, G., Maedche, A.: FCA-merge: Bottom-up merging of ontologies. In: Proc. 17th International Conference on Artificial Intelligence (IJCAI 2001), pp. 225–230 (2001)
Cimiano, P., Hotho, A., Staab, S.: Learning concept hierarchies from text corpora using formal concept analysis. Journal of Artificial Intelligence Research 24, 305–339 (2005)
Nedellec, C.: Corpus-based learning of semantic relations by the ILP system, asium. In: Cussens, J., Džeroski, S. (eds.) LLL 1999. LNCS (LNAI), vol. 1925, pp. 259–278. Springer, Heidelberg (2000)
Völker, J., et al.: Learning disjointness. In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. LNCS, vol. 4519, Springer, Heidelberg (2007)
Haase, P., Völker, J.: Ontology learning and reasoning - dealing with uncertainty and inconsistency. In: da Costa, P.C.G., et al. (eds.) Proc. of the Workshop on Uncertainty Reasoning for the Semantic Web (URSW), pp. 45–55 (2005)
Rudolph, S.: Exploring relational structures via FLE. In: Wolff, K.E., Pfeiffer, H.D., Delugach, H.S. (eds.) ICCS 2004. LNCS (LNAI), vol. 3127, pp. 196–212. Springer, Heidelberg (2004)
Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer, New York (1997) Translator-C. Franzke
Maier, D.: The Theory of Relational Databases. Computer Science Press (1983)
Ganter, B.: Two basic algorithms in concept analysis. Technical Report 831, FB4, TH Darmstadt (1984)
Ganter, B.: Attribute exploration with background knowledge. Theoretical Computer Science 217, 215–233 (1999)
Burmeister, P.: Merkmalimplikationen bei unvollständigem Wissen. In: Lex, W. (ed.) Arbeitstagung Begriffsanalyse und Künstliche Intelligenz, TU Clausthal, pp. 15–46 (1991)
Baader, F., et al.: Completing description logic knowledge bases using formal concept analysis. In: Veloso, M.M. (ed.) IJCAI, pp. 230–235 (2007)
Ehrig, M., Sure, Y.: FOAM - framework for ontology alignment and mapping. results of the ontology alignment initiative. In: Ashpole, B., et al. (eds.) Proc. of the Workshop on Integrating Ontologies, vol. 156, pp. 72–76 (2005)
Sure, Y., et al.: The SWRC ontology - semantic web for research communities. In: Bento, C., Cardoso, A., Dias, G. (eds.) Proc. of the 12th Portuguese Conference on Artificial Intelligence, pp. 218–231. Springer, Heidelberg (2005)
Rudolph, S.: Acqiring generalized domain-range restrictions. In: Proc. of the 6th International Conference on Formal Concept Analysis, Springer, (to appear, 2008)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Völker, J., Rudolph, S. (2008). Lexico-Logical Acquisition of OWL DL Axioms. In: Medina, R., Obiedkov, S. (eds) Formal Concept Analysis. ICFCA 2008. Lecture Notes in Computer Science(), vol 4933. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78137-0_5
Download citation
DOI: https://doi.org/10.1007/978-3-540-78137-0_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78136-3
Online ISBN: 978-3-540-78137-0
eBook Packages: Computer ScienceComputer Science (R0)