Abstract
We present new results of our research on integration of ontologies created automatically by means of Human Language Technologies. The research is related to OLE (Ontology LEarning) – a project aimed at bottom-up generation and merging of ontologies. It utilises a proposal of expressive uncertain knowledge representation framework called ANUIC (Adaptive Net of Universally Interrelated Concepts). We discuss our recent achievements in taxonomy acquisition and show how even simple application of the principles of ANUIC can improve the results of initial knowledge extraction methods. We also suggest an algorithm for large-scale automatic annotation of natural language documents, applying uncertain knowledge bases created using our approach.
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References
Nováček, V., Smrž, P.: Empirical merging of ontologies – a proposal of universal uncertainty representation framework. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 65–79. Springer, Heidelberg (2006)
Gomez-Perez, A., Fernandez-Lopez, M., Corcho, O.: Ontological Engineering. In: Advanced Information and Knowledge Processing. Springer, Heidelberg (2004)
Zhdanova, A.V., Krummenacher, R., Henke, J., Fensel, D.: Community–driven ontology management: Deri case study. In: Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence, pp. 73–79. IEEE Computer Society Press, Los Alamitos (2005)
Buitelaar, P., Cimiano, P., Magnini, B. (eds.): Ontology Learning from Text: Methods, Evaluation and Applications. IOS Press, Amsterdam (2005)
Staab, S., Studer, R. (eds.): Handbook on Ontologies. International Handbooks on Information Systems. Springer, Heidelberg (2004)
Sheth, A., Ramakrishnan, C., Thomas, C.: Semantics for the semantic web: The implicit, the formal and the powerful. International Journal on Semantic Web & Information Systems 1, 1–18 (2005)
Sanchez, E. (ed.): Fuzzy Logic and the Semantic Web. Capturing Intelligence. Elsevier, Amsterdam (2006)
Ryu, P.M., Choi, K.S.: An information-theoretic approach to taxonomy extraction for ontology learning. In: Buitelaar, P., Cimiano, P., Magnini, B. (eds.) Ontology Learning from Text: Methods, Evaluation and Applications, pp. 15–28. IOS Press, Amsterdam (2005)
Hearst, M.A.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the 14th conference on Computational linguistics. Association for Computational Linguistics, Morristown, NJ, USA, pp. 539–545 (1992)
Kanungo, T., Mount, D., Netanyahu, N., Piatko, C., Silverman, R., Wu, A.: An efficient k-means clustering algorithm: analysis and implementation (2002)
Brewster, C., Alani, H., Dasmahapatra, S., Wilks, Y.: Data driven ontology evaluation. In: Proceedings of LREC 2004 (2004)
Klir, G.J., Yuan, B.: Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice-Hall, Englewood Cliffs (1995)
Haase, P., Völker, J.: Ontology learning and reasoning - dealing with uncertainty and inconsistency. In: Proceedings of the URSW2005 Workshop, pp. 45–55 (2005)
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)
Stoilos, G., Stamou, G., Tzouvaras, V., Pan, J., Horrocks, I.: Fuzzy owl: Uncertainty and the semantic web. In: International Workshop of OWL: Experiences and Directions, Galway (2005)
Paritosh, P.K.: The heuristic reasoning manifesto. In: Proceedings of the 20th International Workshop on Qualitative Reasoning (2006)
Hobbs, J.R., Gordon, A.S.: Toward a large-scale formal theory of commonsense psychology for metacognition. In: Proceedings of AAAI Spring Symposium on Metacognition in Computation, pp. 49–54. ACM, Stanford (2005)
Kokinov, B., French, R.M.: Computational models of analogy making. In: Nadel, L. (ed.) Encyclopedia of Conginitve Science, vol. 1, pp. 113–118. Nature Publishing Group, London (2003)
Bechhofer, S., van Harmelen, F., Hendler, J., Horrocks, I., McGuinness, D.L., Patel-Schneider, P.F., Stein, L.A.: OWL Web Ontology Language Reference (2004) (February 2006), http://www.w3.org/TR/owl-ref/
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Nováček, V. (2008). Automatic Knowledge Acquisition and Integration Technique: Application to Large Scale Taxonomy Extraction and Document Annotation. In: Filipe, J., Cordeiro, J., Cardoso, J. (eds) Enterprise Information Systems. ICEIS 2007. Lecture Notes in Business Information Processing, vol 12. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88710-2_13
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DOI: https://doi.org/10.1007/978-3-540-88710-2_13
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