Evaluation of uncertainty in the measurement of sense of natural language constructions

• Published in: International journal of metrology and quality engineering Vol. 8; p. 6
• Main Authors: Bisikalo, Oleg V., Vasilevskyi, Oleksandr M.
• Format: Journal Article
• Language: English
• Published: Les Ulis EDP Sciences 2017
• Subjects: Applications programs; artificial cognitive systems; Automation; Fuzzy sets; Knowledge; Language; language image; lemma; Linguistics; Methods; Natural language; natural language constructions; Order parameters; Semantic analysis; Semantics; sense; Standard deviation; text; Uncertainty; Switzerland
• ISSN: 2107-6847; 2107-6839; 2107-6847
• DOI: 10.1051/ijmqe/2017001

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.