Перегляд за Автор "Matveiev, O. M."

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Development of agent-oriented software components to retrieve the marketing information from the web
(Національний технічний університет «ХПІ», 2018) Cherednichenko, O. Yu.; Melnyk, K. V.; Kirkin, S. V.; Sokolov, D. V.; Matveiev, O. M.; Чередніченко, О. Ю.; Матвєєв, О. М.; Мельник, К. В.; Кіркін, С. В.; Соколов, Д. В.
The article is devoted to researching the processes of extracting marketing information from the Web space. Conclusions are drawn on the need tointroduce an information marketing system into modern business activities. A decision has been taken to develop software for the collection and analysis of marketing information. Identified and analyzed the main problems of collecting marketing information in the Web space. External systems for extracting and processing marketing information from the Web space were considered. During the analysis of the subject area, functional and non-functional requirements for the software being developed were formulated. Requirements for the selection of technologies for the development of an information system were defined. The analysis of software development technologies is carried out and the approach to the development of a software component is chosen. Such approaches to software development as: object-oriented programming, service-oriented architecture, component-oriented programming, agent-oriented programming were analyzed. A decision has been made to use the agent three-tier architecture in software development. The most commonly used programming languages in programming systems were: Java, KIF, KQML, AgentSpeak, April, TeleScript, Tcl/ Tk, Oz. Analyzed such popular agent platforms and their functions as: JADE, Cougaar, ZEUS, Jason. For the development of software, the JADE platform was chosen, its classes, methods and interfaces were examined. The advantages and peculiarities of the SOLID principle are analyzed. In detail, the levels of the CLEAN architecture are examined. And also explained the possibilities of software implementation of this architecture. A software architecture was developed for the data collection system. In accordance with the requirements, a selection of software development tools has been made. It was decided to use the programming language Java, Spring Framework, GoF design pattern, the template Dependency Injection, SOLID and CLEAN architectural principles. A software component was developed for marketing information gathering systems, which allows to optimize this process. The limitations and ways to improve the software system are analyzed.
Multi-Agent Modeling of Project Management Processes in Distributed Teams
(CEUR Workshop Proceedings, 2021) Cherednichenko, O. Yu.; Matveiev, O. M.; Yanholenko, O.; Maneva, R.; Матвєєв, О. М.; Чередніченко, О. Ю.
Changes in the business environment, the innovative nature of projects, lack of necessary skills of project team members lead to increased uncertainty and inability to plan with a given degree of accuracy. Such projects use adaptive project and program management methodologies. In the field of information technology,the use of multi-agent systems is of particular interest. In the context of the use of multi-agent systems for the design of intelligent systems for various purposes, the development and study of a model and software implementation of a prototype of an agent platform are relevant. The aim of this work is to develop and research an agent platform that can be implemented in the work of the distributed team in order to improvetheassignment of tasks. The paper presents the formal agent architecture as a basis of multi-agent model. The task assignment is a case studyto implement and test multi-agent model prototype. The agent platform is developed based on Kotlin programming language. A prototype of the agent platform based on the FIPA specification allows to increase the productivity, scalability and interoperability of multi-agent system.
Towards Classifying HTML-embedded Product Data Based On Machine Learning Approach
(CEUR Workshop Proceedings, 2021) Matveiev, O. M.; Zubenko, A.; Yevtushenko, D.; Cherednichenko, O. Yu.; Матвєєв, О. М.; Чередніченко, О. Ю.
In this paper we explored machine learning approaches using descriptions and titles to classify footwear by brand. The provided data were taken from many different online stores. In particular, we have created a pipeline that automatically classifies product brands based on the provided data. The dataset is provided in JSON format and contains more than 40,000 rows. The categorization component was implemented using K-Nearest Neighbour (K-NN)and Support Vector Machine (SVM) algorithms. The results of the pipeline construction were evaluated basing on the classification report, especially the Precision weighted average value was considered during the calculation, which reached 79.0% for SVM and 72.0% for K-NN.
Моделі формування рекомендацій у інтелектуальних системах електронної комерції
(Харківський національний університет Повітряних Сил імені Івана Кожедуба, 2020) Чередніченко, О. Ю.; Янголенко, О. В.; Іващенко, О. В.; Матвєєв, О. М.; Cherednichenko, O. Yu.; Yanholenko, O.; Ivashchenko, O.; Matveiev, O. M.
Результати роботи пошукових та фільтраційних механізмів сучасних систем електронної комерції не завжди задовольняють вимоги користувачів, що проявляється у неточних та неповних рекомендаціях товарів за пошуковим запитом. Удосконалення якості рекомендацій для покупців онлайн торгівельних платформ є актуальною задачею. Дана робота наводить моделі формування рекомендацій на основі методів кластерного аналізу, які дозволяють згрупувати схожі товари та схожих клієнтів за їхніми характеристиками. Наведені результати експерименту щодо формування рекомендацій придбання рюкзаків для покупців онлайн магазину спортивного обладнання.