Abstract
Ontology Modularization techniques identify coherent and often reusable regions within an ontology. The ability to identify such modules, thus potentially reducing the size or complexity of an ontology for a given task or set of concepts is increasingly important in the Semantic Web as domain ontologies increase in terms of size, complexity and expressivity. To date, many techniques have been developed, but evaluation of the results of these techniques is sketchy and somewhat ad hoc. Theoretical properties of modularization algorithms have only been studied in a small number of cases. This paper presents an empirical analysis of a number of modularization techniques, and the modules they identify over a number of diverse ontologies, by utilizing objective, task-oriented measures to evaluate the fitness of the modules for a number of statistical classification problems.
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
Doran, P., Tamma, V., Iannone, L.: Ontology module extraction for ontology reuse: an ontology engineering perspective. In: CIKM, pp. 61–70. ACM, New York (2007)
Cuenca Grau, B., Horrocks, I., Kazakov, Y., Sattler, U.: Modular reuse of ontologies: Theory and practice. J. of Artificial Intelligence Research (JAIR) 31, 273–318 (2008)
d’Aquin, M., Sabou, M., Motta, E.: Modularization: a key for the dynamic selection of relevant knowledge components. In: First Int.Workshop on Modular Ontologies, ISWC, Athens, Georgia, USA (2006)
Noy, N.F., Musen, M.A.: Specifying ontology views by traversal. In: Int. Semantic Web Conference (2004)
Seidenberg, J., Rector, A.: Web ontology segmentation: analysis, classification and use. In: WWW 2006: Proceedings of the 15th Int. Conference on World Wide Web (2006)
Stuckenschmidt, H., Klein, M.: Structure-based partitioning of large concept hierarchies. In: Proc. of the 3rd Int. Semantic Web Conference, Hiroshima, Japan (2004)
d’Aquin, M., Schlicht, A., Stuckenschmidt, H., Sabou, M.: Ontology modularization for knowledge selection: Experiments and evaluations. In: Wagner, R., Revell, N., Pernul, G. (eds.) DEXA 2007. LNCS, vol. 4653, pp. 874–883. Springer, Heidelberg (2007)
Schlicht, A., Stuckenschmidt, H.: Towards structural criteria for ontology modularization. In: Proceedings of the 1st International Workshop on Modular Ontologies, WoMO 2006, co-located with the International Semantic Web Conference, ISWC 2006, Athens, Georgia, USA, November 5 (2006)
Doran, P., Tamma, V., Payne, T.R., Palmisano, I.: An entropy inspired measure for evaluating ontology modularization. In: 5th International Conference on Knowledge Capture, KCAP 2009 (2009)
Noy, N.F., Musen, M.A.: Prompt: Algorithm and tool for automated ontology merging and alignment. In: Proc. of the 17th National Conference on Artificial Intelligence and 12th Conference on Innovative Applications of Artificial Intelligence (2000)
Doran, P., Tamma, V., Palmisano, I., Payne, T.R.: Dynamic selection of ontological alignments: a space reduction mechanism. In: Twenty-First International Joint Conference on Artificial Intelligence, IJCAI 2009 (2009)
Konev, B., Lutz, C., Walther, D., Wolter, F.: Semantic modularity and module extraction in description logics. In: Proceedings of ECAI 2008: 18th European conference on Artificial Intelligence (2008)
Cohen, W.W., Borgida, A., Hirsh, H.: Computing least common subsumers in description logics. In: AAAI, pp. 754–760 (1992)
Noy, N.F., Musen, M.A.: The PROMPT suite: interactive tools for ontology merging and mapping. International Journal of Human-Computer Studies 59, 983–1024 (2003)
Maedche, A., Staab, S.: Measuring similarity between ontologies. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 251–263. Springer, Heidelberg (2002)
Lutz, C., Walther, D., Wolter, F.: Conservative extensions in expressive description logics. In: IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence, pp. 453–458 (2007)
Cuenca Grau, B., Horrocks, I., Kazakov, Y., Sattler, U.: Just the right amount: Extracting modules from ontologies. In: WWW 2007, Proceedings of the 16th International World Wide Web Conference, Banff, Canada, May 8-12, 2007, pp. 717–727 (2007)
Grau, B.C., Horrocks, I., Kazakov, Y., Sattler, U.: A logical framework for modularity of ontologies. In: IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence, pp. 298–303 (2007)
Borgida, A., Giunchiglia, F.: Importing from functional knowledge bases - a preview. In: Cuenca-Grau, B., Honavar, V., Schlicht, A., Wolter, F. (eds.) WOMO (2007)
d’Aquin, M., Schlicht, A., Stuckenschmidt, H., Sabou, M.: Criteria and evaluation for ontology modularization techniques. In: Stuckenschmidt, H., Parent, C., Spaccapietra, S. (eds.) Modular Ontologies. LNCS, vol. 5445, pp. 67–89. Springer, Heidelberg (2009)
Gangemi, A., Catenacci, C., Ciaramita, M., Lehman, J.: Ontology evaluation and validation. an integrated formal model for the quality diagnostic task. Technical report, Laboratory for Applied Ontology, ISTC-CNR (2005)
Shannon, C.E.: A mathematical theory of communication. Technical Report 27:379-423, 623-656, Bell System Technical Report (1948)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Palmisano, I., Tamma, V., Payne, T., Doran, P. (2009). Task Oriented Evaluation of Module Extraction Techniques. In: Bernstein, A., et al. The Semantic Web - ISWC 2009. ISWC 2009. Lecture Notes in Computer Science, vol 5823. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04930-9_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-04930-9_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04929-3
Online ISBN: 978-3-642-04930-9
eBook Packages: Computer ScienceComputer Science (R0)