Abstract
The article addresses the problem of knowledge representation in digital systems in terms of cognitive science. The authors consider formalized semantic metalanguage as a tool to Simulate the semantic structure of sentences and thoughts. The created on the basis of frame-scenario model SESAME metalanguage is described and discussed, that allows to represent the meaning structure of standard events and situation in an artificial formalized language and combine linguistic and extralinguistic information. SESAME is a “matrix of meanings” for making natural language concepts suitable for “semantic calculations” using computer technology.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bocharov V, Voishvillo E, Dragalin A, Smirnov V (1980) On problems of the evolution of logic. Soviet Stud Philos 18(4):31–52. https://doi.org/10.2753/RSP1061-1967180431
Curry H (1980) Some philosophical aspects of combinatory logic. Stud Logic Found Math 101:85–101. https://doi.org/10.1016/S0049-237X(08)71254-0
Digital economics of the Russian Federation – National program. http://government.ru/rugovclassifier/614/events/. Accessed 10 Feb 2020
Dobrova V, Kistanova O (2017) Meta-languages: nature and characteristic features. Voprosy Kognitivnoy Lingvistiki 1(50):114–117. https://doi.org/10.20916/1812-3228-2017-1-114-117
Faber P, Cabezas-García M (2019) Specialized knowledge representation: from terms to frames. Res Lang 17:197–211. https://doi.org/10.2478/rela-2019-0012
Goddard C, Wierzbicka A (2013) Words and meanings. Oxford University Press, Oxford. https://doi.org/10.1093/acprof:oso/9780199668434.003.0001
Gvishiani N (2017) The metaconcept word-combination and its transformation in English computer-corpus discourse. Voprosy Kognitivnoy Lingvistiki 2:15–25. https://doi.org/10.20916/1812-3228-2017-2-15-25
Jakobson R (1965) Quest for the essence of language. Diogenes 13(51):21–37. https://doi.org/10.1177/039219216501305103
Jakus G, Milutinović V, Omerović S, Tomažič S (2013) Concepts, ontologies, and knowledge representation. Springer, New York. https://doi.org/10.1007/978-1-4614-7822-5_4
Krongauz M (1994) Word formation and linguistics. Russ Linguist 18:379–387. https://doi.org/10.1007/BF01650153
Laurini R (2017) Geographic knowledge infrastructure. ISTE Press, Elsevier, London. https://doi.org/10.1016/b978-1-78548-243-4.50002-5
Lebedev M (2007) Prospects of modern concepts of reliability of knowledge. Voprosy Filosofii 11:119–132
Melchuk I (2015) Dependency in language. In: Wright JD (ed) International encyclopedia of the social & behavioral sciences. Elsevier, London, pp 182–195. https://doi.org/10.1016/b978-0-08-097086-8.53005-0
Melchuk I, Polguère A (2002) A formal lexicon in the meaning – Text theory (or how to do lexica with words). Comput Linguist 13(3–4):261–275
Minsky M (1975) A framework for representing knowledge. In: Winston PH (ed) The psychology of computer vision. McGraw-Hill Book, New York, pp 211–281
Musen M (2014) Knowledge representation. In: Sarkar IN (ed) Methods in biomedical informatics. Academic Press, Cambridge, pp 49–79. https://doi.org/10.1016/b978-0-12-401678-1.00003-8
Nazaruks V, Osis J (2017) A survey on domain knowledge representation with frames. In: Damiani E, Spanoudakis G, Maciaszek L (eds) Proceedings of the 12th international conference on evaluation of novel approaches to software engineering, MDI4SE, vol 1. SciTePress, Porto, pp 346–354. https://doi.org/10.5220/0006388303460354
Solovyev V, Ivanov V (2015) Knowledge-driven event extraction in Russian: corpus-based linguistic resources. Comput Intell Neurosci 2016:4183760. https://doi.org/10.1155/2016/4183760
The Strategy of scientific and technological development of the Russian Federation until 2035. http://kremlin.ru/acts/bank/41449. Accessed 10 Feb 2020
Wierzbicka A (2009) Language and metalanguage: key issues in emotion research. Emot Rev 1:3–14. https://doi.org/10.1177/1754073908097175
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Dobrova, V., Ageenko, N., Menshenina, S. (2021). Semantic Metalanguage for Digital Knowledge Representation. In: Ashmarina, S.I., Mantulenko, V.V. (eds) Current Achievements, Challenges and Digital Chances of Knowledge Based Economy. Lecture Notes in Networks and Systems, vol 133. Springer, Cham. https://doi.org/10.1007/978-3-030-47458-4_12
Download citation
DOI: https://doi.org/10.1007/978-3-030-47458-4_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-47457-7
Online ISBN: 978-3-030-47458-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)