Skip to main content
Log in

The JSM method: A set-theoretical explanation

  • Published:
Automatic Documentation and Mathematical Linguistics Aims and scope

Abstract

An original presentation of the basic concepts and rules of the JSM method is made in terms of conventional set theory (without using the apparatus of non-classical logics). The architecture of the JSM system and its operational principles are considered. The connection between the JSM method and formal concept analysis is discussed. Practical recommendations are given for the developers of non-standard versions of JSM systems.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Finn, V.K., About Possibilities of Formalization of Plausible Reasonings by Multi-Valued Logics Means, Vsesoyuz. simpozium po logike i metodologii nauki, (All-Union Symp. on Logics and Methodology of Science), Kiev, 1976, pp. 82–83.

  2. Finn, V.K., Data Bases with Incomplete Information and New Method of Hypotheses Automatic Generation, in Dialogovye i faktograficheskie sistemy informatsionnogo obespecheniya (Dialogue and Factographic Systems of Information Assurance), Moscow, 1981, pp. 153–156.

  3. Finn, V.K., About Machine-Oriented Formalization of Plausible Reasonings in F. Beckon-J.S. Mill Style, Semiotika I Informatika, 1983, No. 20, pp. 35–101.

  4. Avtomaticheskoe porozhdenie gipotez v intellektual’nykh sistemakh (Hypotheses Automatic Generation in Intellectual Systems), Finn, V.K., Ed., Moscow: LIBROKOM, 2009.

    Google Scholar 

  5. DSM-metod avtomaticheskogo porozhdeniya gipotez: Logicheskie i epistemologicheskie osnovaniya (JSM-Method of Hypotheses Automatic Generation: Logical and Epistemological Foundations), Anshakov, O.M., Ed., Moscow: LIBROKOM, 2009.

    Google Scholar 

  6. Mill, J.S., A System of Logic Ratiocinative and Inductive. Being a Connected View of the Principles of Evidence and the Methods of Scientific Investigation, London: Parker, 1843, 1st ed., 1941, 8th ed.

    Book  Google Scholar 

  7. Popper, K.R., The Logic of Scientific Discovery London: Hutchinson, 1959.

    MATH  Google Scholar 

  8. Peirce, C.S., Abduction and Induction, in Philosophical Writings of Peirce, Buchler, J., Ed., New York: Dover, 1995, pp. 150–156.

    Google Scholar 

  9. Finn, V.K., Inductive Methods of J. S. Mill in Artificial Intellect Systems. Part I, Iskusstvennyi Intellekt I Prinyatie Reshenii, 2010, No. 3, pp. 3–21.

  10. Finn, V.K., Inductive Methods of J. S. Mill in Artificial Intellect Systems. Part II, Iskusstvennyi Intellekt I Prinyatie Reshenii, 2010, No. 4, pp. 14–40.

  11. Finn, V.K., About Determination of Empirical Regularities by Hypotheses Automatic Generation JSM Method, Iskusstvennyi Intellekt I Prinyatie Reshenii, 2010, No. 4, pp. 41–48.

  12. Finn, V.K., Iskusstvennyi intellekt: Metodologiya, primeneniya, filosofiya (Artificial Intellect: Methodology, Applications, Philosophy), Moscow: KRASAND, 2011.

    Google Scholar 

  13. Volkova, A.Yu., Algorithmization of Procedures of the JSM Method for Automatic Hypothesis Generation, Aut. Doc. Math. Lingv., 2011, vol. 45, no. 3, pp.1136–120.

    Google Scholar 

  14. Rosser, J.B. and Turquette, A.R., Many-Valued Logics, Amsterdam: North-Holland, 1951.

    Google Scholar 

  15. Borshchev, V.B., About JSM Method Postulates, in Novosti iskusstvennogo intellekta (Novels of Artificial Intellect), Special Issue to V.K. Finn 60th Anniversary, Moscow, 1993, pp. 16–26.

  16. Anshakov, O.M., About One Interpretation of Hypotheses Automatic Generation JSM Method, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 1999, Nos. 1–2, pp. 45–53.

  17. Shundeev, A.S., Logic-Language Means of Industrial Process Automatization, Candidate Sci. (Phys.-Math.) Dissertation, Moscow, 2005.

  18. Osipov, G.S., Lektsii po iskusstvennomu intellektu (Lectures on Artificial Intellect), Moscow: URSS, 2009.

    Google Scholar 

  19. Lipkin, A.A., Hypotheses Automatic Generation JSM Method for Objects Described by Attributes with Scales, Candidate Sci. (Eng.) Dissertation Moscow, 2008.

  20. Gusakova, S.M., Mikheenkova, M.A., and Finn, V.K., About Logical Means of Meaning Automatization Analysis, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 2001, No. 5, pp. 4–24.

  21. Novikov, F.A. and Ivanov, D.Yu., Modelirovanie na UML. Teoriya, praktika, videokurs (Modeling on UML. Theory, Practice, Videocourse), St. Petersburg: Professional’naya Literatura, Nauka i Tekhnika, 2010.

    Google Scholar 

  22. Shreider, Yu.A., Ravenstvo, skhodstvo, poryadok (Equality, Resemblance, Order), Moscow: Nauka, 1971.

    Google Scholar 

  23. Matematicheskaya Entsiklopediya. T. 1 (A-G) (Mathematical Encyclopedia. Vol. 1. (A-G)) Vinogradov, I.M., Ed., Moscow: Sovetskaya Entsiklopediya, 1977.

    Google Scholar 

  24. Kuznetsov, S.O., JSM-Method on the Galois Equivalence Language, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 2006, No. 12, pp. 1–7.

  25. Vinogradov, D.V., Logical Programs for Quasiaxiomatic Theories, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 1999, Nos. 1–2, pp. 61–64.

  26. Vinogradov, D.V., Correct Logic Programs for Plausible Reasonings, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 2001, No. 5, pp. 25–28.

  27. Mikheenkova, M.A. and Feofanova, T.L., Learning JSM System for Sociological Data Analysis, Vestnik Ros. Gos. Guman. Univ. Ser. Informatika. Informatsionnaya Bezopasnost’. Matematika, 2009, No. 10, pp. 152–169.

  28. Vinogradov, D.V., Formalization of Plausible Reasonings in Logic of First Order Predicates, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 2000, No. 11, pp. 17–20.

  29. Anshakov, O.M., Skvortsov, D.P., and Finn, V.K., About Deductive Imitation of Some Variants of DSM Method, Semiotika I Informatika, 1993, No. 33, pp. 164–233.

  30. Wille, R., Restructuring Lattice Theory: an Approach Based on Hierarchies of Concepts, in Ordered Sets Rival, J., Ed., Boston: Reidel, 1982, pp. 445–470.

    Chapter  Google Scholar 

  31. Ganter, B. and Wille, R., Formal Concept Analysis: Mathematical Foundations, Berlin: Springer-Verlag, 1999.

    Book  MATH  Google Scholar 

  32. Ganter, B. and Wille, R., Conceptual Scaling, in Applications of Combinatorics and Graph Theory to the Biological and Social Sciences, Roberts, F., ed., New York: Springer-Verlag, 1989, pp. 139–167.

    Chapter  Google Scholar 

  33. Anshakov, O.M., Finn, V.K., and Skvortsov, D.P., On Axiomatization of Many-Valued Logics Associated with Formalization of Plausible Reasonings, Studia Logica, 1989, vol. 48, no. 4, pp. 423–447.

    Article  MathSciNet  MATH  Google Scholar 

  34. Pankratova, E.S., Ivashko, V.G., Avidon, V.V., Blinova, V.G., and Bodyagin, D.A., Experimental Testing of New Version of the JSM Method for Automatic Hypothesis Generation, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 1988, No. 2, pp. 18–21.

  35. Pankratova, E.S., Blinova, V.G., and Finn, V.K., About Possibility of JSM Method Application in Chemical Carcinogenezis Identification Problem, in Ekpertnye sistemy: sostoyanie i perspektivy, (Expert Systems: State and Perspectives), Pospelov, D.A., Ed., Moscow: Nauka, 1989, pp. 131–138.

    Google Scholar 

  36. Pankratova, E.S., Ivashko, V.G., Blinova, V.G., and Popov, D.V., Use of Hypotheses Automatic Generation JSM Method for Prognosis of Antineoplastic Activity and Toxicity of Compounds Belonging to Different Classes of Chemical Compounds, in Ekpertnye sistemy: sostoyanie i perspektivy, (Expert Systems: State and Perspectives), Pospelov, D.A., Ed., Moscow: Nauka, 1989, pp. 139–146.

    Google Scholar 

  37. Zabezhailo, M.I., Ivashko, V.G., Kuznetsov, S.O., Mikheenkova, M.A., Khazanovskii, K.P., and Anshakov, O.M., Algorithmic and Program Means of Hypotheses Automatic Generation JSM Method, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 1987, No. 10, pp. 1–14.

  38. Kuznetsov, S.O., Fast Algorithm of Construction of All Intersections of Objects from Finite Half-Lattice, Nauchn. Tekhn. Inform. Ser. 2: Inform. Proc. Syst., 1993, No. 1, pp. 17–20.

  39. Kuznetsov, S.O. and Obiedkov, S.A., Comparing Performance of Algorithms for Generating Concept Lattices, J. Exper. Theor. Artif. Intell., 2002, vol. 14, nos. 2–3, pp. 189–216.

    Article  MATH  Google Scholar 

  40. Norris, E.M., An Algorithm for Computing the Maximal Rectangles in a Binary Relation, Revue Roum. Mathem. Pures Appliq., 1978, no. 23(2), pp. 243–250.

  41. Avidon, V.V., Pomerantsev, I.A., Golender, V.E., and Rozenblit, A.B., Structure-Activity Relationship Oriented Languages for Chemical Structure Representation, J. Chem. Inform. Comp. Sci., 1982, vol. 22, no. 4, pp. 207–214.

    Article  Google Scholar 

  42. Dobrynin D.A. Tool Means for Presentation of Information about Chemical Compound Structure and Their Resemblance in Intellectual Systems, Candidate Sci. (Eng.) Dissertation, Moscow, 2003.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to O. M. Anshakov.

Additional information

Original Russian Text © O.M. Anshakov, 2012, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2, 2012, No. 9, pp. 1–19.

About this article

Cite this article

Anshakov, O.M. The JSM method: A set-theoretical explanation. Autom. Doc. Math. Linguist. 46, 202–220 (2012). https://doi.org/10.3103/S0005105512050020

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0005105512050020

Keywords

Navigation