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Cybernetics and programming
Reference:
Borovskii A.A. —
Prospects for the use of machine learning techniques in processing large volumes of historical data
// Cybernetics and programming.
– 2015. – № 1.
– P. 77 - 114.
DOI: 10.7256/2306-4196.2015.1.13730 URL: https://en.nbpublish.com/library_read_article.php?id=13730
Prospects for the use of machine learning techniques in processing large volumes of historical data
Borovskii Aleksandr Aleksandrovich
Chief Technology Director, LLC "EST"
119034, Rossiya, Moskva, g. Moskva, per. Sechenovskiy, 9, of. 18
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aborovsky@est-it.ru
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DOI: 10.7256/2306-4196.2015.1.13730
Review date:
18-11-2014
Publish date:
20-01-2015
Abstract: In relation to the problems of development of information-analytical platform “The history of modern Russia” the author researches analytical capabilities of the modern methods of machine learning and perspectives of its’ practical use for processing and analyzing large volumes of historical data. The article reviews different strategies of applying machine learning techniques taking into account peculiarities of the studied data. Special attention is given to a problem of interpretability of different types of results, obtained using the machine learning algorithms, as well as the ability to recognize trends and anomalies. As a methodological basis of the research the author uses a theory of information systems, database theory, induction, deduction, comparative, systematic, formal logic, and other methods. The author concludes that the algorithms of machine learning can be used to effectively solve a large class of problems, related to the analysis of historical data, including finding hidden dependencies and patterns. It is noted that establishment of large-scale digital repositories of evidence of historical events makes it possible to examine and analyze the data as a specific time series allowing to investigate the change of state of the social system in time.
Keywords:
history of modern Russia, data analysis, Data Mining, Digital Humanities, machine learning, algorithms, identification of patterns, interpretability of results, time series, anomalies
This article written in Russian. You can find full text of article in Russian
here
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