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An Approach for Ontology Population Based on Information Extraction Techniques

Application to Cultural Heritage (Short Paper)

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On the Move to Meaningful Internet Systems: OTM 2015 Conferences (OTM 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9415))

Abstract

The Colour and Space in Cultural Heritage European (COSCH) COST action has the objective of providing true, precise and complete documentation related to cultural heritage (CH) artifacts. In order to represent and organize knowledge, COSCH developed its own ontology called \(COSCH^{KR}\). This paper proposes an approach for automatically populating this ontology from CH scientific papers. We evaluate our approach in comparing manually annotated and automatically computed triples. Our results show a significant increase of the numbers of generated triples and generated properties.

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References

  1. Maedche, A., Staab, S.: The text-to-onto ontology learning environment. In: Software Demonstration at ICCS-2000-Eight International Conference on Conceptual Structures (2000)

    Google Scholar 

  2. Etzioni, O., Banko, M., Soderland, S., Weld, D.S.: Open information extraction from the web. Communications of the ACM 51(12), 68–74 (2008)

    Article  Google Scholar 

  3. Punuru, J., Chen, J.: Learning non-taxonomical semantic relations from domain texts. Journal of Intelligent Information Systems 38(1), 191–207 (2012)

    Article  Google Scholar 

  4. Flahive, A., Taniar, D., Rahayu, W., Apduhan, B.O.: A methodology for ontology update in the semantic grid environment. Concurrency and Computation: Practice and Experience 27(4), 782–808 (2015)

    Article  Google Scholar 

  5. Morsey, M., Lehmann, J., Auer, S., Stadler, C., Hellmann, S.: Dbpedia and the live extraction of structured data from wikipedia. Program 46(2), 157–181 (2012)

    Article  Google Scholar 

  6. Shekarpour, S., Auer, S.: Rquery: Rewriting text queries to alleviate the vocabulary mismatch problem on rdf knowledge bases

    Google Scholar 

  7. di Buono, M.P., Monteleone, M., Elia, A.: How to populate ontologies. In: Métais, E., Roche, M., Teisseire, M. (eds.) NLDB 2014. LNCS, vol. 8455, pp. 55–58. Springer, Heidelberg (2014)

    Google Scholar 

  8. Pia, M.: Information Extraction for Ontology Population Tasks. An Application to the Italian Archaeological Domain 3(2), 40–50 (2015)

    Google Scholar 

  9. Soon, W.M., Ng, H.T., Lim, D.C.Y.: A machine learning approach to coreference resolution of noun phrases. Computational Linguistics 27(4), 521–544 (2001)

    Article  Google Scholar 

  10. Ng, V., Cardie, C.: Improving machine learning approaches to coreference resolution. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 104–111. Association for Computational Linguistics (2002)

    Google Scholar 

  11. Poon, H., Domingos, P.: Joint unsupervised coreference resolution with markov logic. In: Proceedings of the conference on empirical methods in natural language processing, pp. 650–659. Association for Computational Linguistics (2008)

    Google Scholar 

  12. Stoyanov, V., Cardie, C., Gilbert, N., Riloff, E., Buttler, D., Hysom, D.: Coreference resolution with reconcile. In: Proceedings of the ACL 2010 Conference Short Papers, pp. 156–161. Association for Computational Linguistics (2010)

    Google Scholar 

  13. http://tech.grammarly.com/blog/posts/How-to-Split-Sentences.htm

  14. Rusu, D., Dali, L., Fortuna, B., Grobelnik, M., Mladenic, D.: Triplet extraction from sentences. In: Proceedings of the 10th International Multiconference, pp. 8–12. Information Society-IS (2007)

    Google Scholar 

  15. De Marneffe, M.-C, Manning, C.D.: Stanford typed dependencies manual. 20090110 Httpnlp Stanford 40, 1–22, September 2010

    Google Scholar 

  16. Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: Gate: a framework and graphical development environment for robust nlp tools and applications. In: Proc. 40th Anniversary Meeting of the Association for Computational Linguistics (ACL) (2002)

    Google Scholar 

  17. Fader, A., Soderland, S., Etzioni, O.: Identifying relations for open information extraction. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing, pp. 1535–1545. Association for Computational Linguistics (2011)

    Google Scholar 

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Correspondence to Riyadh Benammar .

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Benammar, R., Trémeau, A., Maret, P. (2015). An Approach for Ontology Population Based on Information Extraction Techniques. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2015 Conferences. OTM 2015. Lecture Notes in Computer Science(), vol 9415. Springer, Cham. https://doi.org/10.1007/978-3-319-26148-5_26

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  • DOI: https://doi.org/10.1007/978-3-319-26148-5_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26147-8

  • Online ISBN: 978-3-319-26148-5

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