Anatoliy Poletaev

• Yaroslavl State University

The article is devoted to the task of the sentiment detection towards an aspect of economic and social development in Russian sentences. The aspect, the attitude to which is determined, can be either explicitly mentioned or implied. The authors investigated possibilities of using neural network classifiers and proposed an algorithm for determining...

The paper compares performance of various methods of automatic implicit aspect detection in publicism sentences in Russian. The task of implicit aspect detection is an auxiliary task in the aspect-oriented sentiment analysis. The experiments were conducted on a corpus of sentences extracted from political campaign materials. The best results, with...

The article is devoted to the task of sentiment detecton of Russian sentences, which is understood as the author’s attitude on the sentence topic expressed through linguistic expression features. Today most studies on this subject utilize texts of colloquial style, limiting the applicability of their results to other styles of speech, particularly...

Automatic syntactic analysis of a sentence is an important computational linguistics task. At present, there are no syntactic structure parsers for Russian that are publicly available and suitable for practical applications. Ground-up creation of such parsers requires building of a treebank annotated according to a given formal grammar, which is qu...

The paper is devoted to construction of a sentence corpus annotated by the general sentiment into 4 classes (positive, negative, neutral, and mixed), a corpus of phrasemes annotated by the sentiment into 3 classes (positive, negative, and neutral), and a corpus of sentences annotated by the presence or absence of irony. The annotation was done by v...

This study is aimed at building an automated model for business writing assessment, based on 14 rubrics that integrate EFL teacher assessment frameworks and identify expected performance against various criteria (including language, task fulfillment, content knowledge, register, format, and cohesion). We developed algorithms for determining the cor...

The article is devoted to the task of sentiment detection of Russian sentences. The sentiment is conceived as the author's attitude to the topic of a sentence. This assay considers positive, neutral, and negative sentiment classes, i.e., the task of three-classes classification is solved. The article introduces a rule-based sentiment detection algo...

The paper describes application of the semantic rule-based sentiment analysis approach, which was earlier developed and tested on English texts, to the Russian language. In order to take into account specificity of Russian it was adapted, particularly representation of the rules as patterns over a list of words was replaced with algorithms over the...

The paper is devoted to automatic detection of rhythm in fiction and investigation of how rhythm of prosaic texts changed over 19th-21st centuries, based on results of such detection. The authors developed algorithms, which extract rhythm figures related to word repetitions (anaphora, epiphora, polysyndeton, etc.), and visualized their statistical...

Optimal portfolio selection is a common and important application of an optimization problem. Practical applications of an existing optimal portfolio selection methods is often difficult due to high data dimensionality (as a consequence of the large number of securities available for investment). In this paper, a method of dimension reduction based...