Кафедра комп’ютерних наук

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https://elar.khmnu.edu.ua/handle/123456789/582

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Перегляд Кафедра комп’ютерних наук за Автор "Hardysh, D."

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  • Ескіз
    Документ
    Datalogic Relation Model for Automated Evaluating the Semantic Integrity of Test Tasks Sets by Machine Learning Means
    (2024) Мазурець, Олександр; Hardysh, D.; Mazurets, O.; Tyschenko, O.
    Datalogic relation model for automated evaluating the semantic integrity of test tasks sets was designed. The developed intelligent system has significant potential for use in educational institutions and organizations where assessing the alignment of test tasks with educational materials is critical. By automating this evaluation process, the system ensures objectivity and reliability in the results.
  • Ескіз
    Документ
    Intelligent System for Automated Assessment of Test Tasks Sets Conformity to Semantic Structure of Educational Materials
    (2024) Мазурець, Олександр; Hardysh, D.; Tyschenko, O.; Mazurets, O.
    Intelligent system for testing knowledge level and analyzing test representativeness of tests was designed and practically implemented in the form of a web platform, which provides the possibility of effective assessment of users' knowledge and skills. The generalized scheme, database datalogic model and component interaction diagram of intelligent system for testing the level of knowledge and analyzing the representativeness of tests were designed. Practical use of the developed platform as tool for self-testing and learning is proposed, which will allow users to check their knowledge, track progress in learning and analyze the representativeness of tests to educational materials.
  • Ескіз
    Документ
    Intelligent System for Automated Assessment of Test Tasks Sets Conformity to Semantic Structure of Educational Materials
    (2024) Hardysh, D.; Klimenko, V.; Mazurets, O.; Мазурець, Олександр Вікторович
    The developed intelligent system for automated assessment of test tasks set conformity to semantic structure of educational materials can have great potential during its use in educational institutions and organizations where it is important to assess the conformity of test tasks to educational materials. It will allow to automate the evaluation process and ensure the objectivity of the results.
  • Ескіз
    Документ
    Neural Network Dual Architecture for Depression Detection Using Cloud Services
    (2024) Tymofiiev, I.; Mazurets, O.; Hardysh, D.; Molchanova, M.; Мазурець, Олександр Вікторович
    A method of detecting a depressive state by means of NLP was developed, which is designed to transform input data in the form of text and a trained neural network model of dual architecture into output data in the form of a numerical assessment of the presence of a depressive state. The proposed method differs from analogs in that it combines a two-stream architecture, which is based on the use of two parallel neural networks, each of which specializes in the analysis of different aspects of the text - syntactic and semantic.