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Systematization and Identification of Semantic Relations in Ontologies for Scientific and Technical Subject Areas

  • N. V. MaksimovEmail author
  • A. S. Gavrilkina
  • V. V. Andronova
  • I. A. Tazieva
Text Processing Automation
  • 1 Downloads

Abstract

This article presents a relations taxonomy constructed on the basis of a conceptual framework, as well as methods of identifying semantic relations that are used for automatically constructing ontologies of subject areas. A predicate lexicon that corresponds to relation types is established through automatically processing a collection of scientific and technical document texts. Patterns of linguistic constructions of semantic relations are constructed in a way that considers morphological features of words and morphemes. Statistics of types of relations and the use of patterns depending on the document type are studied.

Keywords

ontologies text documents semantic relations conceptual framework methods of identifying semantic relations 

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References

  1. 1.
    Van Renssen, A., Gellish: A Generic Extensible Ontological Language, Delft: Delft University Press, 2005.Google Scholar
  2. 2.
    SINTOL, in Sbornik perevodov po voprosam informatsionnoi teorii i praktiki (Collection of Translations on Information Theory and Practice), Moscow: Vses. Inst. Nauchn. Tekh. Inf., 1968, pp. 36–47, 50–52, 66–72, 76–80.Google Scholar
  3. 3.
    Skorokhod’ko, E.F., Linguistic problems of processing theists in automated information retrieval systems, Vopr. Inf. Teor. Prakt., 1974, no.25, pp. 5–120.Google Scholar
  4. 4.
    Winograd, T., Understanding Natural Language, Academic Press, 1976.Google Scholar
  5. 5.
    Maksimov, N.V., The methodological basis of ontological documentary information modeling, Autom. Doc. Math. Linguist., 2018 vol. 52, no.3, pp. 57–72.CrossRefGoogle Scholar
  6. 6.
    Golitsyna, O.L., Maksimov, N.V., Okropishina, O.V., and Strogonov, V.I., The ontological approach to the identification of information in tasks of document retrieval, Autom. Doc. Math. Linguist., 2012, vol. 46, no. 3, pp. 125–132.CrossRefGoogle Scholar
  7. 7.
    Gordei, A.N., The theory of automatic generation of the knowledge architecture (TAPAZ-2) and further minimization of semantic calculi, in Otkrytye semanticheskie tekhnologii proektirovaniya intellektual’nykh sistem. Materialy IV Mezhdunar. nauch.-tekhn. konf. (Minsk, 20–22 fevr. 2014 g.) (Open Semantic Technologies for Intelligent Systems (OSTIS-2014). Proc. IV Int. Sci.-Tech. Conf. (Minsk, February 20–22, 2014)), Minsk, 2014, pp. 49–64.Google Scholar
  8. 8.
    FrameNet project. https://www.framenet.icsi.berkeley.edu/fndrupal/.Google Scholar
  9. 9.
    Hirtz, J., et al., A functional basis for engineering design: Reconciling and evolving previous efforts, Res. Eng. Des., 2002 vol. 13, no. 2, pp. 65–82.CrossRefGoogle Scholar
  10. 10.
    Johansson, I., et al., Functional anatomy: A taxonomic proposal, Acta Biotheor., 2005 vol. 53, no. 3, pp. 153–166.CrossRefGoogle Scholar
  11. 11.
    Smith, B. and Grenon, P., The cornucopia of formalontological relations, Dialectica, 2004, vol. 58, no. 3, pp. 279–296.CrossRefGoogle Scholar
  12. 12.
    Kitamura, Y., Sano, T., Namba, K., and Mizoguchi, R., A functional concept ontology and its application to automatic identification of functional structures, Adv. Eng. Inf., 2002, vol. 16, no. 2, pp. 145–163.CrossRefGoogle Scholar
  13. 13.
    Kitamura, Y. and Mizoguchi, R., Ontology-based systematization of functional knowledge, J. Eng. Des., 2004, vol. 15, no. 4, pp. 327–351.CrossRefGoogle Scholar
  14. 14.
    Kitamura, Y., Koji, Y., and Mizoguchi, R., An ontological model of device function: Industrial deployment and lessons learned, J. Appl. Ontol., 2006, vol. 1, nos. 3–4, pp. 237–262.Google Scholar
  15. 15.
    Apresyan, Yu.D., Fundamental classification of predicates, in Yazykovaya kartina mira i sistemnaya leksikografiya (Language Picture of the World and Systemic Lexicography), Moscow: Yazyki slavyanskikh kul’tur, 2006, pp. 76–110.Google Scholar
  16. 16.
    Vasil’ev, L.M., Teoreticheskie problemy obshchei lingvistiki, slavistiki, rusistiki: Sbornik izbrannykh statei (Theoretical Problems of General Linguistics, Slavic Studies, and Russian Studies: Collection of Selected Papers), Ufa: Red.-Izd. Otd. Bashk. Gos. Univ., 2006.Google Scholar
  17. 17.
    Paducheva, E.V., Dinamicheskie modeli v semantike leksiki (Dynamic Models in the Semantics of Vocabulary), Moscow: Yazyki slavyanskoi kul’tury, 2004.Google Scholar
  18. 18.
    Naikhanova, L.V., Main types of semantic relations between terms of a subject area, Izv. Vyssh. Uchebn. Zaved., Povolzh. Reg., Ser. Tekh. Nauki, Inf. Vychisl. Tekh. Upr., 2008, no. 1, pp. 62–71.Google Scholar
  19. 19.
    Vlasov, D.Yu., Pal’chunov, D.E., and Stepanov, P.A., Automating the extraction of relationships between concepts from natural language texts, Vestn. Novosib. Gos. Univ., Ser.: Inf. Tekhnol., 2010, vol. 8, no. 3, pp. 23–33.Google Scholar
  20. 20.
    Beksaeva, E.A., Research and development of an algorithm for extracting semantic information from the text to form an ontology of a subject area, Nechetkie sistemy i myagkie vychisleniya. Promyshlennye primeneniya. Sb. nauch. trudov IV Vserossiiskoi nauchno-prakticheskoi mul’tikonferentsii s mezhdunarodnym uchastiem “Prikladnye informatsionnye sistemy (PIS-2017)” (Fuzzy Systems and Soft Calculations. Industrial Applications. Proc. IV All-Russian Scientific and Practical Multiconference with International Participation Applied Information Systems (PIS-2017)), Ulyanovsk, 2017, pp. 72–79.Google Scholar
  21. 21.
    Kotel’nikov, D.S. and Lukashevich, N.V., Iterative extraction of event description templates for news clusters, Trudy 14-i Vserossiiskoi nauchnoi konferentsii “Elektronnye biblioteki: Perspektivnye metody i tekhnologii, elektronnye kollektsii”–RCDL-2012, Pereslavl’- Zalesskii, Rossiya, 15–18 oktyabrya 2012 g. (Proc. 14th All-Russian Scientific Conference Electronic Libraries: Advanced Methods and Technologies, Digital Collections (RCDL-2012), Pereslavl-Zalessky, Russia, October 15–18, 2012)), Pereslavl-Zalessky, 2012, pp. 353–359.Google Scholar
  22. 22.
    Bol’shakova, E.I., Language of lexical-syntactic templates LSPL: Usage experience and development paths, Program. Sist. Instrum.: Tematich. Sb., 2014 no. 15, pp. 14–22.Google Scholar

Copyright information

© Allerton Press, Inc. 2018

Authors and Affiliations

  • N. V. Maksimov
    • 1
    Email author
  • A. S. Gavrilkina
    • 2
  • V. V. Andronova
    • 2
  • I. A. Tazieva
    • 2
  1. 1.VINITI (All-Russian Institute of Scientific and Technical Information)Russian Academy of SciencesMoscowRussia
  2. 2.National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)MoscowRussia

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