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Axiomatization of Classes of Domain Cases Based on FCA

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Artificial Intelligence (RCAI 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12412))

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Abstract

The article is devoted to the application of Formal Concept Analysis to the development of domain semantic models. The paper deals with the problem of axiomatization of classes of cases from various domains.

The research is based on the model theoretical approach to the formalization of domains and on Formal Concept Analysis. We consider the four-level semantic model that conceptually describes the given domain. The third level of the semantic model is the set of domain cases. To describe sets of domain cases we use formal contexts; the objects of these formal contexts are models formalizing domain cases. We represent classes of domain cases as classes of models having different signatures. Theories of classes of domain cases and axiomatizable classes of domain cases are investigated. They are defined as intents and extents of formal concepts of the corresponding formal contexts. It is shown that the introduced notion of theory of class of cases, i.e., theory of class containing models with different signatures, is a generalization of the notion of theory of a class of models in the classical sense.

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References

  1. Ganter, B., Wille, R.: Formal Concept Analysis. Springer, Heidelberg (1999). https://doi.org/10.1007/978-3-642-59830-2

    Book  MATH  Google Scholar 

  2. Ganter, B., Stumme, G., Wille, R. (eds.): Formal Concept Analysis. LNCS (LNAI), vol. 3626. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-31881-1

    Book  MATH  Google Scholar 

  3. Kuznetsov, S.O., Poelmans, J.: Knowledge representation and processing with formal concept analysis. Wiley Interdisc. Rev.: Data Mining Knowl. Disc. 3(3), 200–215 (2013)

    Google Scholar 

  4. Poelmans, J., Kuznetsov, S.O., Ignatov, D.I., Dedene, G.: Formal concept analysis in knowledge processing: a survey on models and techniques. Source Doc. Exp. Syst. Appl. 40(16), 6601–6623 (2013)

    Article  Google Scholar 

  5. Buzmakov, A., Kuznetsov, Sergei O., Napoli, A.: Fast generation of best interval patterns for nonmonotonic constraints. In: Appice, A., Rodrigues, P.P., Santos Costa, V., Gama, J., Jorge, A., Soares, C. (eds.) ECML PKDD 2015. LNCS (LNAI), vol. 9285, pp. 157–172. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23525-7_10

    Chapter  Google Scholar 

  6. Kuznetsov, S.O., Makhalova, T.: On interestingness measures of formal concepts. Inf. Sci. 442, 202–219 (2018)

    Article  MathSciNet  Google Scholar 

  7. Makhalova, T., Kuznetsov, S.O., Napoli, A.: MDL for FCA: is there a place for background knowledge? In: CEUR, pp. 45–56 (2018)

    Google Scholar 

  8. Palchunov, D.E.: The solution of the problem of information retrieval based on ontologies. Bisnes-informatika 1(3), 3–13 (2008)

    Google Scholar 

  9. Palchunov, D.E.: Virtual catalog: the ontology-based technology for information retrieval. In: Wolff, K.E., Palchunov, D.E., Zagoruiko, N.G., Andelfinger, U. (eds.) KONT/KPP -2007. LNCS (LNAI), vol. 6581, pp. 164–183. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22140-8_11

    Chapter  Google Scholar 

  10. Shi, W., Barnden, J.A.: Using inductive rules in medical case-based reasoning system. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds.) MICAI 2005. LNCS (LNAI), vol. 3789, pp. 900–909. Springer, Heidelberg (2005). https://doi.org/10.1007/11579427_92

    Chapter  Google Scholar 

  11. Baxter, D., Shepard, D., Siegel, N., Gottesman, B., Schneider, D. Interactive natural language explanations of Cyc inferences. In: AAAI 2005 International Symposium on Explanation-aware Computing (2005)

    Google Scholar 

  12. Lin, R.H., Chuang, C.L.: A hybrid diagnosis model for determining the types of the liver disease. Comput. Biol. Med. 7(40), 665–670 (2010)

    Article  Google Scholar 

  13. Wang, Y., Rudd, A.G., Wolfe, C.D.A.: Age and ethnic disparities in incidence of stroke over time. Stroke 44, 3298–3304 (2013)

    Article  Google Scholar 

  14. Sharaf-El-Deen, D.A., Moawad, I.F., Khalifa, M.E.: A new hybrid case-based reasoning approach for medical diagnosis systems. J. Med. Syst. 2(38), 1–11 (2014)

    Google Scholar 

  15. Naydanov, C., Palchunov, D.E., Sazonova, P.: Development of automated methods for the critical condition risk prevention, based on the analysis of the knowledge obtained from patient medical records. In: Proceedings of the International Conference on Biomedical Engineering and Computational Technologies (SIBIRCON/SibMedInfo—2015), pp. 33–38. IEEE Press (2015)

    Google Scholar 

  16. Palchunov, D.E., Yakhyaeva, G., Yasinskaya, O.: Software system for the diagnosis of the spine diseases using case-based reasoning. Siberian Sci. Med. J. 1(36), 97–104 (2016)

    Google Scholar 

  17. Palchunov, D.E., Tishkovsky, D.E., Tishkovskaya, S.V., Yakhyaeva, G.E.: Combining logical and statistical rule reasoning and verification for medical applications. In: Proceedings of the International Multi-Conference on Engineering, Computer and Information Sciences, (SIBIRCON), pp. 309–313. IEEE Press (2017)

    Google Scholar 

  18. Gumirov V.S., Matyukov P.Y., Palchunov D.E.: Semantic domain-specific languages. In: 2019 International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON), pp. 0955–0960. IEEE Press (2019)

    Google Scholar 

  19. Palchunov D., Yakhyaeva G., Dolgusheva E.: Conceptual methods for identifying needs of mobile network subscribers. In: Proceedings of the Thirteenth International Conference on Concept Lattices and their Applications, CEUR, CEUR Workshop Proceedings, vol. 1624, pp. 147–160. (2016)

    Google Scholar 

  20. Galieva A.G., Palchunov D.E.: Logical methods for smart contract development. In: 2019 International Multi-CONFERENCE on Engineering, Computer and Information Sciences (SIBIRCON), pp. 0881–0885. IEEE Press (2019)

    Google Scholar 

  21. Pal’chunov, D.E.: Lattices of relatively axiomatizable classes. In: Kuznetsov, S.O., Schmidt, S. (eds.) ICFCA 2007. LNCS (LNAI), vol. 4390, pp. 221–239. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-70901-5_15

    Chapter  Google Scholar 

  22. Palchunov D., Yakhyaeva G.: Application of boolean-valued models and FCA for the development of ontological models. In: Proceedings of the 2nd International Workshop on Formal Concept Analysis for Knowledge Discovery (FCA4KD), CEUR, CEUR Workshop Proceedings, vol. 1921, pp. 77–87 (2017)

    Google Scholar 

  23. Palchunov D.E., Yakhyaeva G.E.: Integration of fuzzy model theory and FCA for big data mining. In: 2019 International Multi-conference on Engineering, Computer and Information Sciences (SIBIRCON), pp. 0961–0966. IEEE Press (2019)

    Google Scholar 

  24. Chang, C.C., Keisler, H.J.: Model Theory, 3rd edn. Elsevier Science Pub. Co., North-Holland (1990)

    MATH  Google Scholar 

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Authors and Affiliations

  1. Sobolev Institute of Mathematics, Novosibirsk, Russian Federation

    Dmitry E. Palchunov

  2. Novosibirsk State University, Novosibirsk, Russian Federation

    Dmitry E. Palchunov

Authors
  1. Dmitry E. Palchunov
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Correspondence to Dmitry E. Palchunov .

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Editors and Affiliations

  1. National Research University Higher School, Moscow, Russia

    Sergei O. Kuznetsov

  2. Moscow Institute of Physics and Technology, Dolgoprudny, Russia

    Aleksandr I. Panov

  3. Federal Research Center Computer Science and Control, Moscow, Russia

    Konstantin S. Yakovlev

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Palchunov, D.E. (2020). Axiomatization of Classes of Domain Cases Based on FCA. In: Kuznetsov, S.O., Panov, A.I., Yakovlev, K.S. (eds) Artificial Intelligence. RCAI 2020. Lecture Notes in Computer Science(), vol 12412. Springer, Cham. https://doi.org/10.1007/978-3-030-59535-7_1

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  • DOI: https://doi.org/10.1007/978-3-030-59535-7_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59534-0

  • Online ISBN: 978-3-030-59535-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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