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Vladimir O.
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doi: 10.17586/2226-1494-2020-20-3-382-393

INFORMATION REPRESENTATION METHODS IN SIMPLE SEMANTIC NETWORKS

L. A. Artyushina


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Article in Russian

For citation:
Artyushina L.A. Information representation methods in simple semantic networks. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2020, vol. 20, no. 3, pp. 382–393 (in Russian). doi: 10.17586/2226-1494-2020-20-3-382-393


Abstract
Subject of Research. The paper presents a review of the currently existing basic types of simple semantic networks. We highlight and describe distinguishing features of relations that determine the type of semantic network and the methods of presenting information used in it. Classification of simple semantic networks and corresponding methods by the area of activity has been carried out. The known results are clarified and expanded. Method. The study and analysis of scientific publications on the problem of data representation in information systems provided the identification of distinctive features of the methods related to different types of simple semantic network. Main Results. The concept of a simple semantic network is considered. The mechanisms for the following methods of presenting information in simple semantic networks are described: IS-A, PART-OF, statistical technology, modernized IS-A method; case random, case deterministic, attribute methods, probability of the jth concept occurrence; using the weights of relations between concepts, the proportion of duplicated elements, the importance of concepts; based on the general properties of sets and production rules; setting time frames in relations. The review is based on the Russian-language publications. Practical Relevance. The research results clarify and bring together already known findings that makes it possible to solve the problem of further development of methods for presenting information in semantic networks.

Keywords: semantic networks, information presentation in semantic networks, information presentation methods, intelligent systems

Acknowledgements. This work was performed in Vladimir State University named after Alexander and Nikolay Stoletovs.

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