Analysis of the developed quantitative method for automatic attribution of scientific and technical text content written in Ukrainian

Authors

DOI:

https://doi.org/10.15587/1729-4061.2018.149596

Keywords:

NLP, content monitoring, stop words, content analysis, statistical linguistic analysis, quantitative linguistics

Abstract

A formal approach was proposed to implement text content attribution. The study was conducted with Ukrainian scientific and technical texts. The results of application of the designed algorithms of automatic attribution of the text content based on the NLP and stylemetry methods were analyzed. Prospects and features of application of stylemetry information technologies for attribution of the text content were considered. Quantitative content analysis of scientific and technical text content takes advantage of content monitoring and text content analysis based on NLP, Web-Mining and stylemetry methods to identify the multitude of authors whose talking style is similar to that of the analyzed text fragment. This narrows the range of search for further use in the stylemetry methods to determine the degree of belonging of the analyzed text to a particular author.

Decomposition of the attribution method was carried out based on analysis of such talking coefficients as lexical diversity, degree (measure) of syntactic complexity, talking coherence, indexes of exclusivity and concentration of the text. At the same time, author's style parameters such as the number of words in a certain text, the total number of words of this text, the number of sentences, the number of prepositions, the number of conjunctions, the number of words with occurrence frequency 1, the number of words with occurrence frequency 10 or more were analyzed. Further experimental study requires testing of the proposed method in identifying keywords of texts of other categories: scientific humanitarian, artistic, journalistic, etc.

Author Biographies

Vasyl Lytvyn, Lviv Polytechnic National University S. Bandery str., 12, Lvіv, Ukraine, 79013

Doctor of Technical Sciences, Professor

Department of Information Systems and Networks

Victoria Vysotska, Lviv Polytechnic National University S. Bandery str., 12, Lvіv, Ukraine, 79013

PhD, Associate Professor

Department of Information Systems and Networks

Petro Pukach, Hetman Petro Sahaidachnyi National Army Academy Heroiv Maidanu str., 32, Lviv, Ukraine, 79012

Doctor of Technical Sciences, Professor

Department of Engineering Mechanics (Weapons and Equipment of Military Engineering Forces)

Zinovii Nytrebych, Lviv Polytechnic National University S. Bandery str., 12, Lvіv, Ukraine, 79013

Doctor of Physical and Mathematical Sciences, Professor

Department of Mathematics

Ihor Demkiv, Lviv Polytechnic National University S. Bandery str., 12, Lvіv, Ukraine, 79013

Doctor of Physical and Mathematical Sciences, Associate Professor

Department of Computational Mathematics and Programming

Andriy Senyk, Hetman Petro Sahaidachnyi National Army Academy Heroiv Maidanu str., 32, Lviv, Ukraine, 79012

PhD, Associate Professor

Department of Engineering Mechanics (Weapons and Equipment of Military Engineering Forces)

Oksana Malanchuk, Danylo Halytsky Lviv National Medical University Pekarska str., 69, Lvіv, Ukraine, 79010

PhD

Department of Biophysics

Svitlana Sachenko, Ternopil National Economic University Lvivska str., 11, Ternopil, Ukraine, 46009

PhD

Department of Economic Assessment and Business Audit

Roman Kovalchuk, Hetman Petro Sahaidachnyi National Army Academy Heroiv Maidanu str., 32, Lviv, Ukraine, 79012

PhD, Associate Professor

Department of Engineering Mechanics (Weapons and Equipment of Military Engineering Forces)

Nadiia Huzyk, Hetman Petro Sahaidachnyi National Army Academy Heroiv Maidanu str., 32, Lviv, Ukraine, 79012

PhD

Department of Engineering Mechanics (Weapons and Equipment of Military Engineering Forces)

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Published

2018-12-05

How to Cite

Lytvyn, V., Vysotska, V., Pukach, P., Nytrebych, Z., Demkiv, I., Senyk, A., Malanchuk, O., Sachenko, S., Kovalchuk, R., & Huzyk, N. (2018). Analysis of the developed quantitative method for automatic attribution of scientific and technical text content written in Ukrainian. Eastern-European Journal of Enterprise Technologies, 6(2 (96), 19–31. https://doi.org/10.15587/1729-4061.2018.149596

Issue

Vol. 6 No. 2 (96) (2018): Information technology. Industry control systems

Section

Information technology

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Copyright (c) 2018 Vasyl Lytvyn, Victoria Vysotska, Petro Pukach, Zinovii Nytrebych, Ihor Demkiv, Andriy Senyk, Oksana Malanchuk, Svitlana Sachenko, Roman Kovalchuk, Nadiia Huzyk

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