Skip to main content

Aligning IATE Criminal Terminology to SUMO

  • Conference paper
  • First Online:
Computational Processing of the Portuguese Language (PROPOR 2020)

Abstract

In this paper we apply an ontology matching system in the context of an information extraction project regarding criminal data. Our data comes from social network, in order to make better sense and analysis of the information provided we consider the IATE (InterActive Terminology for Europe) regarding its crime related sub-domain. The alignment of this terminology to an ontology is a further step towards enriching the semantics of the data. We evaluate a recently proposed domain top ontology matcher (based on Wordnet-SUMO previous alignment) to the task of aligning this IATE sub-domain to SUMO, a general purpose top ontology. Another aspect to explore is the use of multi-linguality in the disambiguation problem itself, as in the case of “alvo” (aim as target and not goal) which becomes more clear in the Portuguese than the English version.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://iate.europa.eu/.

  2. 2.

    http://www.loa.istc.cnr.it/old/DOLCE.html.

  3. 3.

    http://ontotext.com/proton.

  4. 4.

    https://github.com/bfo-ontology/BFO/wiki.

  5. 5.

    http://agatha-osi.com/en/.

References

  1. Arp, R., Smith, B., Spear, A.: Building Ontologies with Basic Formal Ontology. MIT Press, Cambridge (2015)

    Book  Google Scholar 

  2. Asprino, L., Basile, V., Ciancarini, P., Presutti, V.: Empirical analysis of foundational distinctions in linked open data. In: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, Stockholm, Sweden, 13–19 July 2018, pp. 3962–3969 (2018). https://doi.org/10.24963/ijcai.2018/551

  3. Brodaric, B., Probst, F.: DOLCE ROCKS: integrating geoscience ontologies with DOLCE. In: Semantic Scientific Knowledge Integration, pp. 3–8 (2008)

    Google Scholar 

  4. Damova, M., Kiryakov, A., Simov, K.I., Petrov, S.: Mapping the central LOD ontologies to PROTON upper-level ontology. In: Workshop on Ontology Matching (2010)

    Google Scholar 

  5. Gangemi, A., Guarino, N., Masolo, C., Oltramari, A., Schneider, L.: Sweetening ontologies with DOLCE. In: Gómez-Pérez, A., Benjamins, V.R. (eds.) EKAW 2002. LNCS (LNAI), vol. 2473, pp. 166–181. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45810-7_18

    Chapter  MATH  Google Scholar 

  6. Gangemi, A., Navigli, R., Velardi, P.: The OntoWordNet project: extension and axiomatization of conceptual relations in WordNet. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) OTM 2003. LNCS, vol. 2888, pp. 820–838. Springer, Heidelberg (2003). https://doi.org/10.1007/978-3-540-39964-3_52

    Chapter  Google Scholar 

  7. Grenon, P., Smith, B., Goldberg, L.: Biodynamic ontology: applying BFO in the biomedical domain. In: Studies in Health Technology and Informatics (2004)

    Google Scholar 

  8. Jain, P., et al.: Contextual ontology alignment of LOD with an upper ontology: a case study with proton. In: Antoniou, G., et al. (eds.) ESWC 2011. LNCS, vol. 6643, pp. 80–92. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21034-1_6

    Chapter  Google Scholar 

  9. Jezek, E.: Sweetening ontologies cont’d: aligning bottom-up with top-down ontologies. In: Proceedings of the Contextual Representation of Events and Objects in Language Workshop (CREOL), Co-located with the Joint Ontology Workshops, JOWO-2019, Graz, Austria (2019)

    Google Scholar 

  10. Jezek, E., Magnini, B., Feltracco, A., Bianchini, A., Popescu, O.: T-PAS; a resource of typed predicate argument structures for linguistic analysis and semantic processing. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation, LREC 2014, Reykjavik, Iceland, 26–31 May 2014, pp. 890–895 (2014)

    Google Scholar 

  11. Keet, C.M.: The use of foundational ontologies in ontology development: an empirical assessment. In: Antoniou, G., et al. (eds.) ESWC 2011. LNCS, vol. 6643, pp. 321–335. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-21034-1_22

    Chapter  Google Scholar 

  12. Lesk, M.: Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. In: Proceedings of the 5th Annual International Conference on Systems Documentation, SIGDOC 1986, pp. 24–26. ACM, New York (1986). https://doi.org/10.1145/318723.318728

  13. Mascardi, V., Cordì, V., Rosso, P.: A comparison of upper ontologies. In: Proceedings of the 8th AI * IA/TABOO Joint Workshop on Agents and Industry, pp. 55–64 (2007)

    Google Scholar 

  14. Mascardi, V., Locoro, A., Rosso, P.: Automatic ontology matching via upper ontologies: a systematic evaluation. IEEE Trans. Knowl. Data Eng. 22(5), 609–623 (2010)

    Article  Google Scholar 

  15. Mika, P., Oberle, D., Gangemi, A., Sabou, M.: Foundations for service ontologies: aligning OWL-S to DOLCE. In: Proceedings of the 13th International Conference on World Wide Web, pp. 563–572 (2004)

    Google Scholar 

  16. Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)

    Article  Google Scholar 

  17. Nardi, J.C., de Almeida Falbo, R., Almeida, J.P.A.: Foundational ontologies for semantic integration in EAI: a systematic literature review. In: Douligeris, C., Polemi, N., Karantjias, A., Lamersdorf, W. (eds.) I3E 2013. IAICT, vol. 399, pp. 238–249. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37437-1_20

    Chapter  Google Scholar 

  18. Navigli, R., Ponzetto, S.P.: BabelNet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network. Artif. Intell. 193, 217–250 (2012)

    Article  MathSciNet  Google Scholar 

  19. Niles, I., Pease, A.: Towards a standard upper ontology. In: Proceedings of the International Conference on Formal Ontology in Information Systems, pp. 2–9 (2001)

    Google Scholar 

  20. Niles, I., Pease, A.: Linking lexicons and ontologies: mapping wordnet to the suggested upper merged ontology. In: Proceedings of the International Conference on Information and Knowledge Engineering, pp. 412–416 (2003)

    Google Scholar 

  21. Pease, A., Benzmüller, C.: Sigma: an integrated development environment for logical theories. AI Commun. 26, 9–97 (2013)

    Article  Google Scholar 

  22. Rebele, T., Suchanek, F.M., Hoffart, J., Biega, J., Kuzey, E., Weikum, G.: YAGO: a multilingual knowledge base from Wikipedia, WordNet, and GeoNames. In: The Semantic Web - ISWC 2016–15th International Semantic Web Conference, Kobe, Japan, 17–21 October 2016, Proceedings, Part II. pp. 177–185 (2016). https://doi.org/10.1007/978-3-319-46547-0_19

    Google Scholar 

  23. Reed, S., Lenat, D.: Mapping ontologies into Cyc. In: Proceedings of the Workshop on Ontologies for the Semantic Web, pp. 1–6 (2002)

    Google Scholar 

  24. Schadd, F.C., Roos, N.: Coupling of wordnet entries for ontology mapping using virtual documents. In: Proceedings of the 7th Conference on Ontology Matching, pp. 25–36 (2012)

    Google Scholar 

  25. Schmidt, D., Basso, R., Trojahn, C., Vieira, R.: Matching domain and top-level ontologies exploring word sense disambiguation and word embedding. In: Emerging Topics in Semantic Technologies (Best Papers from the Workshops at ISWC 2018), pp. 27–38 (2018)

    Google Scholar 

  26. Schmidt, D., Trojahn, C., Vieira, R.: Analysing top-level and domain ontology alignments from matching systems. In: Proceedings of the 11th International Workshop on Ontology Matching Co-located with the 15th International Semantic Web Conference (ISWC 2016), Kobe, Japan, 18 October 2016, pp. 13–24 (2016)

    Google Scholar 

  27. Seppälä, S.: Mapping WordNet to basic formal ontology using the KYOTO ontology. In: Proceedings of the International Conference on Biomedical Ontology, pp. 1–2 (2015)

    Google Scholar 

  28. Silva, V., Campos, M., Silva, J., Cavalcanti, M.: An approach for the alignment of biomedical ontologies based on foundational ontologies. Inf. Data Manag. 2(3), 557–572 (2011)

    Google Scholar 

  29. Terziev, I., Kiryakov, A., Manov, D.: Base Upper-level Ontology (BULO) Guidance. Deliverable 1.8.1, SEKT Project (2005)

    Google Scholar 

  30. Vennesland, A.: Matcher composition for identification of subsumption relations in ontology matching. In: Proceedings of the Conference on Web Intelligence, pp. 154–161 (2017)

    Google Scholar 

  31. Wang, P.: Lily results on SEALS platform for OAEI 2011. In: Proceedings of the 6th International Workshop on Ontology Matching, pp. 156–162 (2011)

    Google Scholar 

  32. Yatskevich, M., Giunchiglia, F.: Element level semantic matching using WordNet. In: Meaning Coordination and Negotiation Workshop, pp. 37–48 (2004)

    Google Scholar 

  33. Zong, N., Nam, S., Eom, J.H., Ahn, J., Joe, H., Kim, H.G.: Aligning ontologies with subsumption and equivalence relations in linked data. Knowl. Based Syst. 76(1), 30–41 (2015). https://doi.org/10.1016/j.knosys.2014.11.022

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Daniela Schmidt .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Schmidt, D., Dal Bosco, A., Trojahn, C., Vieira, R., Quaresma, P. (2020). Aligning IATE Criminal Terminology to SUMO. In: Quaresma, P., Vieira, R., Aluísio, S., Moniz, H., Batista, F., Gonçalves, T. (eds) Computational Processing of the Portuguese Language. PROPOR 2020. Lecture Notes in Computer Science(), vol 12037. Springer, Cham. https://doi.org/10.1007/978-3-030-41505-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-41505-1_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-41504-4

  • Online ISBN: 978-3-030-41505-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics