Abstract
We propose an application of a statistical relational learning method as a means for automatic detection of semantic correspondences between concepts of OWL ontologies. The presented method is based on an algebraic data representation which, in contrast to well-known graphical models, imposes no arbitrary assumption with regard to the data model structure. We use a probabilistic relevance model as the basis for the estimation of the most plausible matches.We experimentally evaluate the proposed method employing datasets developed for the Ontology Alignment Evaluation Initiative (OAEI) Anatomy track, for the task of identifying matches between concepts of AdultMouse Anatomy ontology and NCI Thesaurus ontology on the basis of expert matches partially provided to the system.
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References
Ciesielczyk, M., Szwabe, A.: RI-based Dimensionality Reduction for Recommender Systems. In: Proc. of 3rd International Conference on Machine Learning and Computing, IEEE Press, Singapore (2011)
De Raedt, L.: Logical and Relational Learning. Springer (2008)
Dietterich, T., Domingos, P., Getoor, L., Muggleton, S., Tadepalli, P.: Structured Machine Learning: the Next Ten Years. Machine Learning 73(1), 3–23 (2008)
Euzenat, J., Ferrara, A., Meilicke, C., Nikolov, A., Pane, J., Scharffe, F., Shvaiko, P., Stuckenschmidt, H., Svb-Zamazal, O., Svtek, V., Trojahn dos Santos, C.: Results of the Ontology Alignment Evaluation Initiative 2010. In: Proc. of 5th ISWC Workshop on Ontology Matching (OM), Shanghai, pp. 85–117 (2010)
Franz, T., Schultz, A., Sizov, S., Staab, S.: Triplerank: Ranking Semantic Web Data by Tensor Decomposition. In: The Semantic Web-ISWC 2009, pp. 213–228 (2009)
Getoor, L., Taskar, B.: Introduction to Statistical Relational Learning. The MIT Press (2007)
Haenni, R.: Towards a Unifying Theory of Logical and Probabilistic Reasoning. In: ISIPTA, pp. 193–202 (2005)
Nickel, M., Tresp, V., Kriegel, H.-P.: A Three-Way Model for Collective Learning on Multi-Relational Data. In: Proceedings of the 28th International Conference on Machine Learning (2011)
Singh, A.P., Gordon, G.J.: Relational Learning via Collective Matrix Factorization. In: Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 650–658 (2008)
Struyf, J., Blockeel, H.: Relational Learning. In: Sammut, C., Webb, G. (eds.) Encyclopedia of Machine Learning, pp. 851–857. Springer (2010)
Sutskever, I., Salakhutdinov, R., Tenenbaum, J.B.: Modelling Relational Data Using Bayesian Clustered Tensor Factorization. In: Advances in Neural Information Processing Systems, vol. 22 (2009)
Szwabe, A., Ciesielczyk, M., Misiorek, P.: Long-Tail Recommendation Based on Reflective Indexing. In: Wang, D., Reynolds, M. (eds.) AI 2011. LNCS, vol. 7106, pp. 142–151. Springer, Heidelberg (2011)
van Rijsbergen, C.J.: The Geometry of Information Retrieval. Cambridge University Press, New York (2004)
Ontology Alignment Evaluation Initiative, Campaign (2011), http://oaei.ontologymatching.org/2011/
W3C. Web Ontology Language (OWL), http://www.w3.org/2004/OWL
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Szwabe, A., Misiorek, P., Walkowiak, P. (2012). Reflective Relational Learning for Ontology Alignment. In: Omatu, S., De Paz Santana, J., González, S., Molina, J., Bernardos, A., RodrÃguez, J. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent and Soft Computing, vol 151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28765-7_62
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DOI: https://doi.org/10.1007/978-3-642-28765-7_62
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