Abstract
When multiple ontologies are used within one application system, aligning the ontologies is a prerequisite for interoperability and unhampered semantic navigation and search. Various methods have been proposed to compute mappings between elements from different ontologies, the majority of which being based on various kinds of similarity measures. As a major shortcoming of these methods it is difficult to decode the semantics of the results achieved. In addition, in many cases they miss important mappings due to poorly developed ontology structures or dissimilar ontology designs. I propose a complementary approach making massive use of relation extraction techniques applied to broad-coverage text corpora. This approach is able to detect different types of semantic relations, dependent on the extraction techniques used. Furthermore, exploiting external background knowledge, it can detect relations even without clear evidence in the input ontologies themselves.
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Aleksovski, Z., Klein, M.C.A., ten Kate, W., van Harmelen, F.: Matching unstructured vocabularies using a background ontology. In: Staab, S., Svátek, V. (eds.) EKAW 2006. LNCS (LNAI), vol. 4248, pp. 182–197. Springer, Heidelberg (2006)
Aronson, A.R.: Effective mapping of biomedical text to the Umls Metathesaurus: The MetaMap program. In: Proceedings of the AMIA 2001, pp. 17–21 (2001)
Beisswanger, E., Hahn, U.: JULIE Lab’s UIMA Collection Reader for Wikipedia. In: Proceedings of the LREC 2010 Workshop on New Challenges for NLP Frameworks, pp. 15–19 (2010)
Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Cyganiak, R., Hellmann, S.: DBpedia - a crystallization point for the web of data. Web Semantics 7(3), 154–165 (2009)
Ciaramita, M., Gangemi, A., Ratsch, E., Saric, J., Rojas, I.: Unsupervised learning of semantic relations between concepts of a molecular biology ontology. In: Proceedings of the IJCAI 2005, pp. 659–664 (2005)
Cimiano, P.: Ontology Learning and Population from Text: Algorithms, Evaluation and Applications. Springer, Heidelberg (2006)
Euzenat, J., Ferrara, A., Hollink, L., Isaac, A., Joslyn, C., Malaisé, V., Meilicke, C., Nikolov, A., Pane, J., Sabou, M., Scharffe, F., Shvaiko, P., Spiliopoulos, V., Stuckenschmidt, H., Sváb-Zamazal, O., Svátek, V., dos Santos, C.T., Vouros, G.A., Wang, S.: Results of the Ontology Alignment Evaluation Initiative 2009. In: Proceedings of the ISWC 2009 Workshop on Ontology Matching (2009)
Euzenat, J., Shvaiko, P.: Ontology matching. Springer, Heidelberg (2007)
Girju, R., Badulescu, A., Moldovan, D.: Automatic discovery of part-whole relations. Computational Linguistics 32(1), 83–135 (2006)
Hahn, U., Buyko, E., Landefeld, R., Mühlhausen, M., Poprat, M., Tomanek, K., Wermter, J.: An overview of JCoRe, the JULIE Lab UIMA component repository. In: Proceedings of the LREC 2008 Workshop on UIMA for NLP, pp. 1–7 (2008)
Hearst, M.A.: Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the ACL 1992 Conference, pp. 539–545 (1992)
Medelyan, O., Milne, D., Legg, C., Witten, I.H.: Mining meaning from Wikipedia. International Journal of Human-Computer Studies 67(9), 716–754 (2009)
Nastase, V., Strube, M., Boerschinger, B., Anas, E.: WikiNet: A very large scale multi-lingual concept network. In: Proceedings of the LREC 2010 (2010)
Navigli, R.: Word sense disambiguation: A survey. ACM Computing Surveys 41(2), 1–69 (2009)
Ponzetto, S.P., Strube, M.: Deriving a large scale taxonomy from Wikipedia. In: Proceedings of the AAAI 2007 Conference, pp. 1440–1445 (2007)
Reynaud, C., Safar, B.: Exploiting WordNet as background knowledge. In: Proceedings of the ISWC 2007 Workshop on Ontology Matching (2007)
Sanderson, M., Croft, W.B.: Deriving concept hierarchies from text. In: Proceedings of the SIGIR 1999 Conference, pp. 206–212 (1999)
Seddiqui, M.H., Aono, M.: An efficient and scalable algorithm for segmented alignment of ontologies of arbitrary size. Web Semantics 7(4), 344–356 (2009)
Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., Goldberg, L., Eilbeck, K., Ireland, A., Mungall, C.J., Leontis, N., Rocca-Serra, P., Ruttenberg, A., Sansone, S.A., Scheuermann, R.H., Shah, N., Whetzel, P.L., Lewis, S.E.: The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nature Biotechnology 25(11), 1251–1255 (2007)
Snow, R., Jurafsky, D., Ng, A.Y.: Learning syntactic patterns for automatic hypernym discovery. In: Advances in Neural Information Processing Systems 17, pp. 1297–1304. MIT Press, Cambridge (2005)
Suchanek, F.M., Sozio, M., Weikum, G.: SOFIE: A Self-Organizing Framework for Information Extraction. In: Proceedings of the WWW 2009 Conference (2009)
Van Hage, W.R., Katrenko, S., Schreiber, G.: A method to combine linguistic ontology-mapping techniques. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 732–744. Springer, Heidelberg (2005)
Völker, J., Haase, P., Hitzler, P.: Learning expressive ontologies. In: Proceedings of the 2008 Conference on Ontology Learning and Population, pp. 45–69 (2008)
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Beisswanger, E. (2010). Exploiting Relation Extraction for Ontology Alignment. In: Patel-Schneider, P.F., et al. The Semantic Web – ISWC 2010. ISWC 2010. Lecture Notes in Computer Science, vol 6497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17749-1_19
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