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Sistemy i Sredstva Inform., 2018, Volume 28, Issue 2, Pages 128–144 (Mi ssi577)  

This article is cited in 1 scientific paper (total in 1 paper)

Methodology of reversible generalization in context of classification of information transformations

I. M. Zatsman

Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation

Abstract: An approach to the problem of creating a methodology for the reversible generalization of information objects (RGIO) as the processes of their concrete-abstract transformations is proposed. From the theoretical point of view, the description of the processes of generalization of information objects makes it possible to enrich the classification of information transformations in the domain of informatics by including a class of concrete-abstract transformations into it. It is important to emphasize that in the paper, informatics is treated according to the scientific paradigm of Paul Rosenbloom as a complex of scientific disciplines that studies information transformations in technical, living, and social systems, and not just in computers and networks. From the applied point of view, the description of generalization processes in the Rosenbloom paradigm enriches the foundations of developing information systems that implement concrete-abstract transformations. The description of the problem of creating the RGIO-methodology is illustrated by the processes of generalization of bilingual annotations in a supracorpora database (SCDB). The reversibility of the processes of annotation generalization is the basis for a multifaceted and verifiable statistical analysis of arrays of annotations formed in the SCDB.

Keywords: supracorpora database; generalization of information objects; information transformations; class of concrete-abstract transformations; annotation generalization.

Funding Agency Grant Number
Russian Science Foundation 16-18-10004
The study was performed at the FRC CSC RAS and supported by the Russian Science Foundation (project 16-18-10004).


DOI: https://doi.org/10.14357/08696527180210

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Received: 11.03.2018

Citation: I. M. Zatsman, “Methodology of reversible generalization in context of classification of information transformations”, Sistemy i Sredstva Inform., 28:2 (2018), 128–144

Citation in format AMSBIB
\Bibitem{Zat18}
\by I.~M.~Zatsman
\paper Methodology of reversible generalization in context of classification of information transformations
\jour Sistemy i Sredstva Inform.
\yr 2018
\vol 28
\issue 2
\pages 128--144
\mathnet{http://mi.mathnet.ru/ssi577}
\crossref{https://doi.org/10.14357/08696527180210}
\elib{http://elibrary.ru/item.asp?id=34954057}


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    Citing articles on Google Scholar: Russian citations, English citations
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    This publication is cited in the following articles:
    1. D. A. Nikishin, “Protsessy generalizatsii v analogovoi i tsifrovoi kartografii”, Sistemy i sredstva inform., 28:3 (2018), 204–216  mathnet  crossref  elib
  • Системы и средства информатики
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