Abstract
An increasing number of applications benefits from light-weight ontologies, or to put it differently “a little semantics goes a long way”. However, our experience indicates that more expressiveness can offer significant advantages. Introducing disjointness axioms, for instance, greatly facilitates consistency checking and the automatic evaluation of ontologies. In an extensive user study we discovered that proper modeling of disjointness is a difficult and very time-consuming task. We therefore developed an approach to automatically enrich learned or manually engineered ontologies with disjointness axioms. This approach relies on several methods for obtaining syntactic and semantic evidence from different sources which we believe to provide a solid base for learning disjointness. After thoroughly evaluating the implementation of our approach we think that in future ontology engineering environments the automatic discovery of disjointness axioms may help to increase the richness, quality and usefulness of any given ontology.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Bisson, G., Nedellec, C., Canamero, L.: Designing clustering methods for ontology building - The Mo’K workbench. In: Proc. of the ECAI Ontology Learning Workshop, pp. 13–19 (2000)
Paslaru Bontas Simperl, E., Tempich, C., Sure, Y.: ONTOCOM: A cost estimation model for ontology engineering. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 625–639. Springer, Heidelberg (2006)
Buitelaar, P., Olejnik, D., Sintek, M.: OntoLT: A protégé plug-in for ontology extraction from text. In: Proc. of the 2nd Int. Semantic Web Conference, ISWC’03 (2003)
Cimiano, P., Völker, J.: Text2onto – a framework for ontology learning and data-driven change discovery. In: Montoyo, A., Muńoz, R., Métais, E. (eds.) NLDB 2005. LNCS, vol. 3513, pp. 227–238. Springer, Heidelberg (2005)
Cimiano, P.: Towards large-scale, open-domain and ontology-based named entity classification. In: Angelova, G., Bontcheva, K., Mitkov, R., Nicolov, N. (eds.) Proc. of the International Conference on Recent Advances in Natural Language Processing (RANLP), Borovets, Bulgaria, September 2005, pp. 166–172. INCOMA Ltd. (2005)
Fellbaum, C.: WordNet, an electronic lexical database. MIT Press, Cambridge (1998)
Freund, Y., Mason, L.: The alternating decision tree learning algorithm. In: ICML, pp. 124–133 (1999), http://www.lsmason.com/papers/ICML99-AlternatingTrees.pdf
Guarino, N., Welty, C.A.: A formal ontology of properties. In: Knowledge Acquisition, Modeling and Management, pp. 97–112 (2000), citeseer.nj.nec.com/guarino00formal.html
Haase, P., Völker, J.: Ontology learning and reasoning - dealing with uncertainty and inconsistency. In: Proc. of the Workshop on Uncertainty Reasoning for the Semantic Web (URSW), pp. 45–55 (2005)
Harris, Z.: Distributional structure. In: Katz, J. (ed.) The Philosophy of Linguistics, pp. 26–47. Oxford University Press, New York (1985)
Kozaki, K., Sunagawa, E., Kitamura, Y., Mizoguchi, R.: Fundamental considerations of role concepts for ontology evaluation. In: Proc. of the Workshop EON – Evaluation of Ontologies for the Web (2006)
Maedche, A., Staab, S.: Ontology learning for the semantic web. IEEE IS 16(2) (2001)
Navigli, R., Velardi, P., Cucchiarelli, A., Neri, F.: Extending and enriching WordNet with OntoLearn. In: Proc. of the GWC 2004, pp. 279–284 (2004)
Quinlan, J.R.: C4.5 Programs for Machine Learning. Morgan Kaufmann, San Francisco (1993)
Rector, A.L., Drummond, N., Horridge, M., Rogers, J.D., Knublauch, H., Stevens, R., Wang, H., Wroe, C.: OWL pizzas: Practical experience of teaching OWL-DL: Common errors & common patterns. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds.) EKAW 2004. LNCS (LNAI), vol. 3257, pp. 63–81. Springer, Heidelberg (2004)
Rose, T., Stevenson, M., Whitehead, M.: The reuters corpus volume 1-from yesterday’s news to tomorrow’s language resources. In: Proc. of the Third International Conference on Language Resources and Evaluation, pp. 29–31 (2002)
Schlobach, S.: Debugging and semantic clarification by pinpointing. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 226–240. Springer, Heidelberg (2005)
Schutz, A., Buitelaar, P.: RelExt: A tool for relation extraction from text in ontology extension. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 593–606. Springer, Heidelberg (2005)
Terziev, I., Kiryakov, A., Manov, D.: Base upper-level ontology (BULO) guidance. SEKT deliverable 1.8.1, Ontotext Lab, Sirma AI EAD, Ltd. (2004)
Völker, J., Vrandečić, D., Sure, Y.: Automatic evaluation of ontologies (AEON). In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 716–731. Springer, Heidelberg (2005)
Vrandečić, D., Pinto, H.S., Sure, Y., Tempich, C.: The DILIGENT knowledge processes. Journal of Knowledge Management 9(5), 85–96 (2005)
Wang, T.D.: Gauging ontologies and schemas by numbers. In: Proc. of the Workshop EON – Evaluation of Ontologies for the Web (2006)
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann Series in Data Management Sys., Morgan Kaufmann, San Francisco (2005)
Wu, Z., Palmer, M.: Verb semantics and lexical selection. In: 32nd. Annual Meeting of the Ass. for Computational Linguistics, New Mexico, pp. 133–138 (1994), citeseer.ist.psu.edu/wu94verb.html
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Völker, J., Vrandečić, D., Sure, Y., Hotho, A. (2007). Learning Disjointness. In: Franconi, E., Kifer, M., May, W. (eds) The Semantic Web: Research and Applications. ESWC 2007. Lecture Notes in Computer Science, vol 4519. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72667-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-72667-8_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72666-1
Online ISBN: 978-3-540-72667-8
eBook Packages: Computer ScienceComputer Science (R0)