ISSN 0021-3454 (print version)
ISSN 2500-0381 (online version)

vol 63 / May, 2020

DOI 10.17586/0021-3454-2019-62-8-702-709

UDC 004.415.2


I. A. Bessmertny
ITMO University, Saint Petersburg, 197101, Russian Federation; Associate Professor

A. V. Vasiljev
ITMO University, Faculty of Software Engineering and Computer Technique;

J. A. Koroleva
ITMO University; postgraduate

A. V. Platonov
ITMO University, Faculty of Software Engineering and Computer Technique ;

E. A. Poleschuk
ITMO University, Faculty of Software Engineering and Computer technic;

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Abstract. Creation of intelligent systems in the paradigm of logical decision-making requires formalization of knowledge in the form of ontologies, production models, etc. However, a rigorous formalization of knowledge is far from always possible due to the incompleteness, inaccuracy, and inconsistency of the data. In this regard, recently, the attention of researchers has shifted to extracting knowledge from natural language texts. Particularly noteworthy is the recently developing approach based on the use of quantum formalism to the objects of the macrocosm, which allows one to consider the uncertainty and inaccuracy inherent in the natural language. Numerous experiments conducted over the past 30 years demonstrate that the mathematical apparatus developed for modeling elementary particles also satisfactorily describes the behavior of people, which cannot be described by the mathematical apparatus of classical logic and probability theory. A review of the methods of processing natural language texts by means of quantum mathematics is presented. The methods are designed to eliminate the shortcomings of existing methods and means of information retrieval.
Keywords: intelligent systems, quantum formalism, processing of natural language texts, modeling of semantics, density operator

  1. Boroday S.Yu. Voprosy Jazykoznanija, 2013, no. 4, pp. 17–54. (in Russ.)
  2. Caputo A., Piwowarski B., Lalmas M. Proceedings of the 2nd Italian Information Retrieval Workshop, 2011, January.
  3. Hitzler P., Krtzsch M., Rudolph S. Foundations of Semantic Web Technologies, Chapman & Hall/CRC, 2009.
  4. Amerland D. Google Semantic Search: Search Engine Optimization Techniques That Get Your Com-pany More Traffic, Increase Brand Impact, and Amplify Your Online Presence, Que Publishing Com-pany, 2013, рр. 40–53.
  5. Clark S., Coecke B., Sadrzadeh M. Quantum Interaction, California, USA, 2007.
  6. Blacoe W., Kashefi E., Lapata M. Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, June 9–14, 2013, Atlanta, Georgia, USA, Association for Computational Linguistics, 2013, March, рр. 847–857. DOI: 10.1016/j.physa.2016.03.003
  7. Li J., Zhang P., Song D., Hou Y. Physica A: Statistical Mechanics and its Applications, 2016, March. DOI: 10.1016/j.physa.2016.03.003.
  8. Hrennikov A.J. Vvedenie v kvantovuju teoriju informacii (Introduction to The Quantum Information Theory), Moscow, 2008, рр. 97–107.
  9. Lambek J. Logical Aspects of Computational Linguistics, Berlin, Heidelberg, Springer, 1999, vol. 27, рр. 1–27.
  10. Abramsky S., Duncan R. Mathematical Structures in Computer Science, 2006, no. 3(16), pp. 469–489.
  11. Sordoni A., Nie J., Bengio Y. Proceedings of the 36th International ACM SIGIR Conference on Re-search and Development in Information Retrieval. SIGIR’13, NY, USA, ACM, 2013, рр. 653–662.
  12. Sordoni A., Bengio Y., and Nie J.-Y. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014, рр. 1586–1582.
  13. D’Hooghe B., Aerts D., Haven E. VUB, CLEA, 2008, 228568348_Quantum_formalisms_in_non-quantum_physics_situations_historical_developments_and_directions_for_future_research.
  14. Blacoe W., Kashefi E., Lapata M. Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, USA, Association for Computational Linguistics, 2013, рр. 847–857, qs08/abstracts08/ Haven.pdf.
  15. Clark S., Coecke B., Grefenstette E. et al. Malaysian Journal of Mathematical Sciences, 2013, vol. 8.
  16. Rijsbergen C. J. van. The Geometry of Information Retrieval, NY, USA, Cambridge University Press, 2004. ISBN: 0521838053.
  17. Gabora L., Aerts D. J. Exp. Theor. Art. Int., 2002, vol. 31, рр. 327–358.
  18. Barros J., Toffano Z., Meguebli Y., Doan B. Quantum Interaction, 7th International Conference, UK, 2013, vol. 8369, рр. 110–121.
  19. Robins J.M., Vanderweele T.J. and Gill R.D. Scand, 2015, J. Stat. biostats.bepress:cobra/83.
  20. Sordoni A., Nie J.-Y. Quantum Interaction. QI 2013. Lecture Notes in Computer Science, 2014, vol. 8369, рр. 147–159,
  21. Bell J.S. Physics, 1964, no. 3(1), pp. 195–200,
  22. Guido Fano, Blinder S.M. Springer international publishing, 2017, vol. 262.
  23. Aerts D., Czachor M., Sozzo S. CoRR, 2011, vol. 10, рр. 35–40.
  24. Galofaro F., Toffano Z., Doan B. Kybernetes, 2018, no. 2(47), pp. 307–320,
  25. Lund K., Burgess C. Behavior Research Methods Instruments and Computers, 1996, vol. 28, рр. 203–208.
  26. Yan Xin, Li Xue, Song Dawei, Computational and Information Science. Lecture Notes in Computer Science, Berlin, Springer, 2004, рр. 711–717.
  27. Hou Y., Song D. International Symposium on Quantum Interaction, Springer, 2009, рр. 237–250.
  28. Hou Y., Zhao X., Song D., Li W. ACM Transactions on Information Systems (TOIS), 31. 12.2013.