Models and algorithms for complex analysis of large corpuses of Russian poetic texts

We propose the algorithm of automated definition of the genre type and semantic characteristics of poetic texts in Russian. We formulated the approaches to the construction of a joint (“two-dimensional”) classifier of genre types and stylistic colouring of poetic texts, based on the definition of interdependence of the type of genre and stylistic colouring of the text. On the basis of these approaches the principles of formation of the training samples for the algorithms for the definition of styles and genre types were analysed. The computational experiments were conducted using the corpus of texts of A. S. Pushkin\u27s Lyceum lyrics to select the most accurate algorithm for classifying poetic texts, including using the most well-known techniques for ensembling basic algorithms in composition, such as weighted voting, boosting and stacking, and single words, bigrams and trigrams were used as characteristic features of poems

Modeling of electricity consumption in the systems with smart equipment

Big data is the foundation of modern energy management systems. There are two energy consumption models where systems are one of the consumers with intelligent equipment: static and dynamic. The dynamic model uses a two-tariff closed-loop accounting scheme, which implies changes in tariffs based on the analysis of current consumption. The results of an experimental study of both models using energy consumption data are presented. The influence of the number of such devices on the possibility of achieving uniform consumption when using the second model is shown. Usage of machine learning for generation a consumption forecast based on time series is show

Determination of the Features of the Author’s Style of A.S. Pushkin’s Poems by Machine Learning Methods

This paper presents the study of the author’s style of A.S. Pushkin based on the comparison of his poetic texts with the texts of contemporary poets. The purpose of this study is to determine the features of the author’s style of A.S. Pushkin using machine learning methods. This paper describes the construction of several classifications based on different groups of features, as well as the classification based on a combined set of features from different groups. The quality of all constructed classifications is also analyzed; special attention is paid to the interpretation of the neural network solution and the identification of features of the author’s style

Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts

In this paper we propose the algorithm of automated definition of the genre type and semantic characteristics of poetic texts in Russian. We formulated the approaches to the construction of a joint (“two-dimensional”) classifier of genre types and stylistic colouring of poetic texts, based on the definition of interdependence of the type of genre and stylistic colouring of the text. On the basis of these approaches the principles of formation of the training samples for the algorithms for the definition of styles and genre types were analyzed. The computational experiments with a corpus of texts of the Lyceum lyrics of A.S.Pushkin were implemented, which showed good results in determining the stylistic colouring of poetic texts and sufficient results in determining the genres. The proposed algorithms can be used for automation of the complex analysis of Russian poetic texts, significantly facilitating the work of the expert in determining their styles and genres by providing appropriate recommendations

Development of Intellectual Web System for Morph Analyzing of Uzbek Words

Currently, there is an active development of the Uzbek sector of the Internet. In it, as in other national sectors, the most common form of presentation of textual information is semi-structured documents, work that presupposes the availability of reliable algorithms for text analysis, including its lexical characteristics. The article offers an intelligent web application developed for morphological analysis of words in the Uzbek language. The web application is based on the concept of generation and stem analysis of the Uzbek language word forms. A well-known Porter algorithm was chosen as the basis for stemming. The morphoanalyzer generates word forms of the Uzbek language based on the division of words into certain classes, taking into account the specifics and structure of this language. For example, nouns can be classified by meaning (related, nominal), by quantity (singular and plural), by case, and also, by the endings of belonging (possessive)

Automated Determination of the Type of Genre and Stylistic Coloring of Russian Texts

In this paper we propose the algorithm of automated definition of the genre type and semantic characteristics of poetic texts in Russian. We formulated the approaches to the construction of a joint (“two-dimensional”) classifier of genre types and stylistic colouring of poetic texts, based on the definition of interdependence of the type of genre and stylistic colouring of the text. On the basis of these approaches the principles of formation of the training samples for the algorithms for the definition of styles and genre types were analyzed. The computational experiments with a corpus of texts of the Lyceum lyrics of A.S.Pushkin were implemented, which showed good results in determining the stylistic colouring of poetic texts and sufficient results in determining the genres. The proposed algorithms can be used for automation of the complex analysis of Russian poetic texts, significantly facilitating the work of the expert in determining their styles and genres by providing appropriate recommendations

Determination of the Features of the Author’s Style of A.S. Pushkin’s Poems by Machine Learning Methods

This paper presents the study of the author’s style of A.S. Pushkin based on the comparison of his poetic texts with the texts of contemporary poets. The purpose of this study is to determine the features of the author’s style of A.S. Pushkin using machine learning methods. This paper describes the construction of several classifications based on different groups of features, as well as the classification based on a combined set of features from different groups. The quality of all constructed classifications is also analyzed; special attention is paid to the interpretation of the neural network solution and the identification of features of the author’s style

The Question of Studying Information Entropy in Poetic Texts

One of the approaches to quantitative text analysis is to represent a given text in the form of a time series, which can be followed by an information entropy study for different text representations, such as “symbolic entropy”, “phonetic entropy” and “emotional entropy” of various orders. Studying authors’ styles based on such entropic characteristics of their works seems to be a promising area in the field of information analysis. In this work, the calculations of entropy values of the first, second and third order for the corpus of poems by A.S. Pushkin and other poets from the Golden Age of Russian Poetry were carried out. The values of “symbolic entropy”, “phonetic entropy” and “emotional entropy” and their mathematical expectations and variances were calculated for given corpora using the software application that automatically extracts statistical information, which is potentially applicable to tasks that identify features of the author’s style. The statistical data extracted could become the basis of the stylometric classification of authors by entropy characteristics

Mathematical simulation of heat transfer at deciduous tree ignition by cloud-to-ground lightning discharge

Numerical research results of deciduous tree ignition by cloud-to-ground lightning discharge are presented. The problem is solved in one-dimensional statement in cylindrical system of coordinates. The typical range of influence parameters of positive and negative cloud-to-ground lightning discharges is considered. Ignition conditions for deciduous tree are established

Usage of modern computer technologies in the learning process of the philologists of complex analysis of Russian poetic texts

In this article we present the algorithms of the automated analysis of metrical, strophic and concordance characteristics of Russian poetic texts, realized in the form of processing software of the poetic texts, which can be an important learning tool for philologists in comprehensive analysis of the poems. The results of the such of analysis will allow to expand essentially the possibilities of the philologists who study as the listed levels of verses, as their semantic and pragmatic characteristics, and also to free the philologists from routine work, to expand the range of analyzed works by reducing the dependence of the quality of the comparative analysis on the personal knowledge of the researcher, and also to apply the different methods of intellectual analysis of data