Int. J. Metrol. Qual. Eng.
Volume 8, 2017
|Number of page(s)||8|
|Published online||21 February 2017|
Evaluation of uncertainty in the measurement of sense of natural language constructions
Dean of the Faculty of Computer Systems and Automation, Vinnytsya National Technical University,
95 Khmelnitskoye Shose,
2 Department of Metrology and Industrial Automation, Vinnytsya National Technical University, 95 Khmelnitskoye Shose, Vinnitsya 21021, Ukraine
⁎ Corresponding author: firstname.lastname@example.org
Accepted: 4 January 2017
The task of evaluating uncertainty in the measurement of sense in natural language constructions (NLCs) was researched through formalization of the notions of the language image, formalization of artificial cognitive systems (ACSs) and the formalization of units of meaning. The method for measuring the sense of natural language constructions incorporated fuzzy relations of meaning, which ensures that information about the links between lemmas of the text is taken into account, permitting the evaluation of two types of measurement uncertainty of sense characteristics. Using developed applications programs, experiments were conducted to investigate the proposed method to tackle the identification of informative characteristics of text. The experiments resulted in dependencies of parameters being obtained in order to utilise the Pareto distribution law to define relations between lemmas, analysis of which permits the identification of exponents of an average number of connections of the language image as the most informative characteristics of text.
Key words: sense / uncertainty / text / natural language constructions / artificial cognitive systems / language image / lemma
© O.V. Bisikalo and O.M. Vasilevskyi, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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