Том 51, № 3 (2017)

The basic terms of metascience and philosophy of science are considered. In their context, we give the definitions of science, a field of science, and two adjacent sciences in relation to computer science: mathematics and technology. We determine the status of computer science as a formal field of science, which consists of theories, in each of which the following constructive conceptual transition is accomplished: the principles of algorithmic computations–programming paradigms–programs–running programs on computers.

This paper describes the software implementation of the VKF method for data mining that was successfully applied to two datasets from UCI Machine Learning Repository. A simplified version of the VKF system for searching for a random subset demonstrated an impressive speed of its operation. The theoretical result explaining the observed phenomenon will be proven. The general case is not yet amenable to such an analysis; however, even in the general case the speed of operation is very high.

The problem of the development of an architectural project and a mathematical model for storing confidential information in centers for processing general purpose data is discussed.

This paper considers various features for extracting named entities from texts in Russian, which are used within the approaches based on machine learning, including the features of a token itself (lexeme), as well as vocabulary, contextual, cluster, and two-stage features. The contribution of each feature to improving the quality of extraction of named entities is studied. The CRF-classifier is used as a method of machine learning in the experiments that are described in this paper. The contribution of features is compared based on two open collections using the F-measure.

This paper considers an algorithm for revealing the multiword combinations and derivative prepositions that are characteristic of Russian business and official speech. The construction of such an algorithm can be considered as a necessary stage of studying business and official speech. The described mechanism can be useful in compiling textbooks, training, and controlling services for both foreigners and native speakers of the Russian language. A word list in the form of an Excel file is created based on the core of collocations that have been already included in existing tutorials. The orders of public authorities published in the public domain on the Internet are used as texts over which the search is made.

This article draws on the example of business texts to consider practical aspects of the distortion of meaning in translation from one language to another in the available machine translation (MT) systems and their underlying approach based on word-by-word translation. An integrated functional approach to translating business texts is suggested on the basis of analyzing semantic and morphological features of actual text content and also on axiological and epistemic semantic features that bring to light subjective modality. The suggested technique is used to develop an algorithm of business text MT that makes it possible to resolve the word-by-word translation issue and conveys the meanings of short texts. Cases of testing the suggested technique and the derived algorithm are considered for the Russian–English language pair.