Персона: Антонов, Евгений Вячеславович
Загружается...
Email Address
Birth Date
Научные группы
Организационные подразделения
Организационная единица
Институт международных отношений
Цель ИМО и стратегия развития - системная подготовка высококвалифицированных кадров, способных решать нестандартные задачи при реализации международных научно-технологических и торгово-промышленных проектов для компаний и корпораций ключевых секторов экономики страны.
Статус
Фамилия
Антонов
Имя
Евгений Вячеславович
Имя
7 results
Результаты поиска
Теперь показываю 1 - 7 из 7
- ПубликацияТолько метаданныеGraph visualization of the characteristics of complex objects on the example of the analysis of politicians(2020) Ulizko, M.; Tukumbetova, R.; Antonov, E.; Artamonov, A.; Антонов, Евгений Вячеславович; Артамонов, Алексей Анатольевич© 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).The paper considers the task of analyzing complex interconnected objects using graph construction. There is no unified tool for constructing graphs. Some solutions can build graphs limited by the number of nodes, while others do not visually display data. The Gephi application was used to construct graphs for the research. Gephi has great functionality for building and analyzing graphs. The subject of research is a politician with a certain set of characteristics. In the paper an algorithm that enables to automate data collection on politicians was developed. One of the main methods of data collecting on the Internet is web scraping. Web scraping software may access the World Wide Web directly using the HTTP, or through a web browser. While web scraping can be done manually by a software user, the term typically refers to automated processes implemented using a software agent. The data was necessary for constructing graphs and their analysis. The use of graphs enables to see various types of relationships, including mediate. This methodology enables to change the attitude towards the analysis of multidimensional objects.
- ПубликацияТолько метаданныеThe visualization of educational measurement results in adaptive eLearning systems for the analysis of the assessment materials quality(2021) Lavdina, Y.; Gustun, O.; Antonov, E.; Лавдина, Юлия Константиновна; Густун, Олег Николаевич; Антонов, Евгений Вячеславович© 2021 Copyright for this paper by its authors.In the adaptive eLearning system educational measurements are used to control the learning process realized on the feedback approach. Based on the current educational measurements results of the students’ achievements the decision is made on the formation of the educational content given to them at the next stage of learning. To obtain reliable and accurate assessments of the students’ educational achievements, it is necessary to use assessment materials that satisfy the requirements for reliability, homogeneity, discriminatory power, validity and other characteristics. In order to evaluate the values of these quality indicators of assessment tools, it is necessary to do sufficient statistical research of the educational measurements results. At the same time the researcher often encounters the situation when the measurement data are insufficient to achieve the required significance level of the conclusions obtained. In this case assistance in the control decision support can be acquired by analyzing the visual presentation of the educational measurements results. We propose the visual presentation of the assessment materials characteristics, which helps to evaluate the values of quality indicators of assessment tools during the accumulation of new measurement data. This information combined with a visual analysis of the results of students’ achievements makes it possible to identify the trends in the changes of dynamics in students’ competencies and to form the educational control action corresponding to their academic performance levels.
- ПубликацияТолько метаданныеEvaluation of Named Entity Recognition Software Packages for Data Mining(2024) Sokolov, I.; Antonov, E.; Artamonov, A.; Соколов, Иван Дмитриевич; Антонов, Евгений Вячеславович; Артамонов, Алексей Анатольевич
- ПубликацияТолько метаданныеDesigning a System for Monitoring the Publication Activity of the Scientific Organization(2024) Malugin, M.; Antonov, E.; Artamonov, A.; Малугин, Матвей Игоревич; Антонов, Евгений Вячеславович; Артамонов, Алексей Анатольевич
- ПубликацияТолько метаданныеNew challenges and opportunities in technology-assisted phraseology interpreting: the case of Yandex live stream translation Novos desafios e oportunidades na interpretacao da fraseologia assistida pela tecnologia: o caso da traducao de video ao vivo do Yandex(2025) Rodriguez, P. R.; Antonov, E.; Антонов, Евгений Вячеславович
- ПубликацияОткрытый доступEvaluating the Effectiveness of Machine Learning Methods for Spam Detection(2021) Kontsewaya, Y.; Antonov, E.; Artamonov, A.; Антонов, Евгений Вячеславович; Артамонов, Алексей Анатольевич© 2020 Elsevier B.V.. All rights reserved.Technological advances are accelerating the dissemination of information. Today, millions of devices and their users are connected to the Internet, allowing businesses to interact with consumers regardless of geography. People all over the world send and receive emails every day. Email is an effective, simple, fast, and cheap way to communicate. It can be divided into two types of emails: spam and ham. More than half of the letters received by the user - spam. To use Email efficiently without the threat of losing personal information, you should develop a spam filtering system. The aim of this work is to reduce the amount of spam using a classifier to detect it. The most accurate spam classification can be achieved using machine learning methods. A natural language processing approach was chosen to analyze the text of an email in order to detect spam. For comparison, the following machine learning algorithms were selected: Naive Bayes, K-Nearest Neighbors, SVM, Logistic regression, Decision tree, Random forest. Training took place on a ready-made dataset. Logistic regression and NB give the highest level of accuracy - up to 99%. The results can be used to create a more intelligent spam detection classifier by combining algorithms or filtering methods.
- ПубликацияОткрытый доступAgent data merging(2020) Antonov, E.; Lopatina, E.; Ionkina, K.; Tretyakov, E.; Антонов, Евгений Вячеславович; Ионкина, Кристина Вячеславовна© 2020 The Authors. Published by Elsevier B.V.The present article deals with data collection in a given field using the agent-based technologies from various information sources of the Internet with the aim to ob-tain reliable and up-to-date data. The agent-based approach is illustrated by the data collection on the nuclear power plants operating all over the world. Three open information sources have been selected for data extraction. The information sources concerned have been analyzed and the features of data provision structure identified. In the course of the present work the following tools for the develop-ment of the software agents have been described: The browser control for human behavior simulation, HTML markup analysis using the XPath query language and data extraction from PDF-documents using regular expressions. Above all, the article considers the software architecture and the database scheme. In the re-sult of the software operation, data regarding 789 nuclear power plants has been obtained.