Перегляд за Автор "Melnyk, K. V."
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Документ Automated system for the creation and replenishment of users' electronic lexicographical resources(Society for Cultural and Scientific Progress in Central and Eastern Europe, 2018) Borysova, N. V.; Melnyk, K. V.This article proposes a solution to improve the efficiency of automated generation of electronic lexicographical resources based on strongly-structured electronic information arrays processing. The developed automated information system for lexicographical resources creation and replenishment have been described is this article. Several supporting subsystems of developed automated system have been characterized. The effectiveness of the information system has been evaluated.Документ Automation of employee evaluation in educational institution(Odessa National Academy of Food Technologies, 2019) Melnyk, K. V.; Borysova, N. V.; Melnyk, V. I.Документ Design of a mobile application for monitoring the condition of patients with epilepsy(Національний технічний університет "Харківський політехнічний інститут", 2023) Slonevskyi, Y. O.; Liutenko, Iryna Victorivna; Melnyk, K. V.Документ Development of a web-based application for delivering the "Software testing" course(Одеська національна академія харчових технологій, 2023) Miroshnychenko, D. I.; Melnyk, K. V.; Liutenko, Iryna VictorivnaThe use of the developed web application will allow for a reduction in time and an increase in convenience for delivering and learning the "Software Testing" course, as well as provide an additional tool for presenting theoretical material and assessing students' knowledge.Документ Development of agent-oriented software components to retrieve the marketing information from the web(НТУ "ХПІ", 2018) Cherednichenko, Olga Yurevna; Melnyk, K. V.; Kirkin, Stanislav Vasylevich; Sokolov, Dmitry Vitalevich; Matveev, Alexander NikolaevichThe article is devoted to researching the processes of extracting marketing information from the Web space. Conclusions are drawn on the need to introduce 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.Документ Development of computer system for adaptive knowledge testing in humanitarian disciplines(Дніпровський національний університет ім. О. Гончара, 2019) Borysova, N. V.; Melnyk, K. V.; Melnyk, V. I.Документ Efficiency estimation of methods for sentiment analysis of social network messages(Національний технічний університет "Харківський політехнічний інститут", 2019) Borysova, N. V.; Melnyk, K. V.The results of effectiveness evaluating of machine learning methods for sentiment analysis of social network messages are presented in this paper. The importance of the sentiment analysis problem as one of the important tasks of natural language processing in general and text ual information processing in particular is substantiated. A review of existing methods and software for sentiment analysis are ma de. The choice of classifiers for sentiment analysis of texts for this research is substantiated. The principles of functioning of a Naïve Bayesian Classifier and classifier based on a recurrent neural network are described. Classifiers were sequentially trained in two corpuses: first, in the RuTweetCorp corpus, the corpus of short messages from the social network Twitter, and then on the Slang corpus, the corpus of messages from social networks Facebook and Instagram and posts from the Pikabu website, second corpus have been marked up the tonality of slang words. Information about the tonality of slang words was taken from the youth slang dictionary obtained as a result of the survey of users. The separation of texts by tonality was carried out into three c lasses: positive, negative and neutral. The efficiency of these classifiers was evaluated. Efficiency evaluation was carried out according to standard metrics Recall, Precision, F-measure, Accuracy. For the naive Bayesian classifier, after training on the first corpus, the following metric values were obtained: Recall = 0,853; Precision = 0,869; F-measure = 0,861; Accuracy = 0,855; and after training on the second corpus such values were obtained: Recall = 0,948; Precision = 0,975; F-measure = 0,961; Accuracy = 0,960. For the classifier based on a recurrent neural network, after training on the first corpus, the following metric values were obtained: Recall = 0,870; Precision = 0,878; F-measure = 0,874; Accuracy = 0,861; and after training on the second corpus such values were obtained: Recall = 0,965; Precision = 0,982; F-measure = 0,973; Accuracy = 0,973. These results prove that additional training on the second corpus increased the efficiency of classifiers by 10–11%.Документ Improving the quality of credit activity by using scoring model(Запорізький національний технічний університет, 2019) Melnyk, K. V.; Borysova, N. V.Context. The problem of credit assessment of a client is considered. It is a simultaneous processing of lender’s data of different nature with further definition of the credit rating. The object of this study was the process of lending to individuals by credit institutions. Objective. The purpose of the work is to study the process of improving the quality of lending through the development and use of a scorecard model. Method. An analytical review of the domain area was conducted. A business process model for assessing clients’ creditworthiness in the form of an IDEF0 diagram is developed. Dedicated groups of indicators characterizing a potential lender from different directions. Selected sets of values for each indicator of credit separately. The methods of solving the problem of clients’ creditworthiness are analyzed. Selected Bayesian naive classifier as a method for solving the problem of classification of potential lenders. The existing information systems for assessing the creditworthiness of clients are analyzed. A scoring model for assessing credit ratings by the client in the form of an algorithm is developed. The list of functional requirements of the information system, which is presented in the form of a use case diagram is determined. Three-level architecture for the information system is proposed. A database model has been developed to preserve customer information. An information system was developed for determining the credit rating of a client based on the developed scoring model. Numerous studies have been conducted to determine the class of a potential creditor. The process of determining the quality of credit activity is analyzed. Quality indicators for assessing the creditworthiness of clients are selected. The method of calculating the quality of credit activity is offered. Results. The scoring model was developed, which was used in solving the credit assessment of clients through the help of the proposed information system. The process of improving the quality of credit rating is investigated. Conclusions. The conducted experiments have confirmed the proposed scoring model and allow recommending it for use in practice for assessment process of client creditworthiness. Scientific novelty is to improve the process of credit activity by automating the use of naïve Bayes classifier, which reduces the human factor in decision-making.Документ Intelligent Data Processing in Creating Targeted Advertising(National Technical University "Kharkiv Polytechnic Institute", 2017) Kirkin, S.; Melnyk, K. V.Документ Methodical recommendation to "Basics of software engineering. Laboratory practice". Part 1(National Technical University "Kharkiv Polytechnic Institute", 2019) Melnyk, K. V.; Borisova, N. V.; Lutenko, I. V.; Ershova, S. I.; Smolin, P. A.; Grinchenko, Marina AnatoliyvnaSoftware engineering is an engineering discipline that is concerned with all aspects of software production. Software engineering can be divided into sub-disciplines. Some of them are: - Software engineering management: The application of management activities – planning, coordinating, measuring, monitoring, controlling, and reporting – to ensure that the development and maintenance of software is systematic, disciplined, and quantified. Requirements engineering: The elicitation, analysis, specification, and validation of requirements for software.Документ Methodical recommendation to "Basics of software engineering. Laboratory practice". Part 2(National Technical University "Kharkiv Polytechnic Institute", 2019) Melnyk, K. V.; Borisova, N. V.; Lutenko, I. V.; Ershova, S. I.; Smolin, P. A.; Grinchenko, Marina AnatoliyvnaSoftware engineering is an engineering discipline that is concerned with all aspects of software production. Software engineering can be divided into sub-disciplines. Some of them are: - Software engineering management: The application of management activities – planning, coordinating, measuring, monitoring, controlling, and reporting – to ensure that the development and maintenance of software is systematic, disciplined, and quantified.- Requirements engineering: The elicitation, analysis, specification, and validation of requirements for software.Документ Methodical recommendation to "Basics of software engineering. Laboratory practice". Part 3(National Technical University "Kharkiv Polytechnic Institute", 2019) Melnyk, K. V.; Borisova, N. V.; Lutenko, I. V.; Ershova, S. I.; Smolin, P. A.; Grinchenko, Marina AnatoliyvnaSoftware engineering is an engineering discipline that is concerned with all aspects of software production. Software engineering can be divided into sub-disciplines. Some of them are: - Software engineering management: The application of management activities – planning, coordinating, measuring, monitoring, controlling, and reporting – to ensure that the development and maintenance of software is systematic, disciplined, and quantified. Requirements engineering: The elicitation, analysis, specification, and validation of requirements for software.Документ Model of the monitoring process for early diagnosis of patients' health(2021) Melnyk, K. V.; Borysova, N. V.; Smolin, P. A.; Dehtiarova, Iryna; Gasan, Iuliia; Voida (Alpatova), AllaThis research paper presents an approach for resolving the monitoring task for early diagnosis process of patient’s health. The problem of the monitoring task for different sphere of life is considered. The model of the monitoring process has been developed in the form of an activity diagram. The analysis of existing medical information system for clinical monitoring is conducted. The analytical review of mathematical methods for resolving the monitoring task in medicine has been made. The BPMN-model of the monitoring for early diagnosis process has been formalized. Experimental studies were carried out on the example of determining the presence or absence of diabetes mellitus in a patient. The list of risk factors and set of symptoms of type 2 of diabetes mellitus have formed. The quality criteria have been chosen. The integral quality factor is proposed. The assessment process of the quality of the monitoring task for early diagnosis process indicates that developed method would determine the improving of the medical decision process.Документ Rasch model usage for testing results assessment(Національний технічний університет "Харківський політехнічний інститут", 2019) Melnyk, K. V.; Borysova, N. V.