Рекомендаційна система планування дозвілля в умовах карантину

dc.citation.epage144
dc.citation.issue11
dc.citation.journalTitleВісник Національного університету "Львівська політехніка". Інформаційні системи та мережі
dc.citation.spage127
dc.contributor.affiliationНаціональний університет “Львівська політехніка”
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.authorВерес, Олег
dc.contributor.authorЛевус, Яна
dc.contributor.authorVeres, Oleh
dc.contributor.authorLevus, Yana
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2023-08-17T06:36:03Z
dc.date.available2023-08-17T06:36:03Z
dc.date.created2022-03-01
dc.date.issued2022-03-01
dc.description.abstractДосліджено проблему планування організації дозвілля у періоди вимушеного перебування вдома із використанням засобів інформаційних технологій. У роботі описано проблеми, які виникають у мешканців міст під час карантинних обмежень, та їх вплив на психоемоційне здоров’я людини. Визначено потребу в адаптації та модифікації звичних форм активності дозвілля до нового формату, оскільки найвідоміші сучасні інформаційні системи, які надають послуги із дозвілля, є вузькоспеціалізованими. Вони генерують рекомендації, які пов’язані з медіа-сервісами. Досліджено методи надання рекомендацій. Для вирішення проблемної ситуації побудовано дерево цілей. Розглянуто альтернативні засоби реалізації інформаційної системи. За допомогою методу аналізу ієрархії (МАІ) вибрано оптимальний тип системи для реалізації пропонованого рішення – рекомендаційну систему. Описано алгоритм роботи рекомендаційної системи, що пропонує альтернативи проведення вільного часу у періоди вимушеного перебування вдома. Використано механізм зваженого гібриду для надання рекомендацій. Для створення портрета користувача використано метод індикаторів типів особистості. За допомогою засобів мови UML спроєктовано концептуальну модель системи. Для реалізації прототипу мобільного застосунку системи вибрано мови програмування Java, JavaScript, фрейморк React Native. Для роботи із базою даних вибрано систему управління бази даних MySQL. Наведено приклад використання системи у вигляді мобільного застосунку. Описано основні етапи взаємодії користувача із рекомендаційною системою, що сприяє організації проведення вільного часу в періоди вимушеного перебування вдома. Робота рекомендаційної системи спрямована на послаблення негативних наслідків перебування у режимі вимушеного карантину на психоемоційний стан людини. Особливістю рекомендацій розробленого прототипу інформаційної системи є надання пропозицій, які містять, окрім пасивних видів проведення дозвілля, також активні, що враховують особливості кожного її користувача. Застосування рекомендаційної системи не обмежується лише карантинним чинником. Послугами рекомендаційної системи доцільно скористатись людям з обмеженими можливостями, після фізичних травм, що призвели до тимчасової малорухомості, та в період реабілітації від їх наслідків.
dc.description.abstractThe work is devoted to research on the problem of management and organization of free time during the period of forced stay at home by means of information technologies. The paper describes the problems during quarantine restrictions and how this affects the psychoemotional health of the person. The need to adapt and modify the usual forms of leisure activity to the new format has been determined. The most famous modern information systems, providing entertainment services are narrow-purpose systems. They generate recommendations related to media services. Methods of providing recommendations have been studied. A tree of goals was built to solve the problem situation. Alternative means of implementation of the information system are considered. Using the method of the hierarchical analysis, the optimal system type of implementation of the proposed solution is chosen – the recommendation system. The algorithm of work of the recommendation system of free time during the period of forced stay at home is described. The mechanism of weight optimization in the weighted hybrid recommendation algorithm was used to provide recommendations. When a user's portrait is created, the method of the personality type indicator is used. Using the UML language tools, a conceptual system model has been designed. For realization of the prototype of a mobile application of the system language programming Java, JavaScript, frame react Native is chosen. To work with the database the MySQL database management system has been selected. An example of using the system as a mobile application is given. The main stages of interaction of the user with the recommended system of free time during the period of forced stay at home are described. The work of the recommendation system is aimed at mitigating the negative consequences on the psycho-emotional state of a person who is in the conditions of forced quarantine. The special feature of the recommendations of the developed prototype is to offer, in addition to passive activities, active actions that take into account the peculiarities of each user. Application of the system is not limited only to quarantine. The services of the system will be appropriate for people with disabilities, in the case of physical injury transfer or liquidation, which led to temporary immobility.
dc.format.extent127-144
dc.format.pages18
dc.identifier.citationВерес О. Рекомендаційна система планування дозвілля в умовах карантину / Олег Верес, Яна Левус // Вісник Національного університету "Львівська політехніка". Інформаційні системи та мережі. — Львів : Видавництво Львівської політехніки, 2022. — № 11. — С. 127–144.
dc.identifier.citationenVeres O. Recommendation system for planning leisure in quarantine conditions / Oleh Veres, Yana Levus // Visnyk Natsionalnoho universytetu "Lvivska politekhnika". Informatsiini systemy ta merezhi. — Lviv : Lviv Politechnic Publishing House, 2022. — No 11. — P. 127–144.
dc.identifier.doidoi.org/10.23939/sisn2022.11.127
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/59482
dc.language.isouk
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofВісник Національного університету "Львівська політехніка". Інформаційні системи та мережі, 11, 2022
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dc.relation.referencesen28.Beheshti, A., Yakhchi, S., Mousaeirad, S., Ghafari, S. M., Goluguri, S. R., & Edrisi, M. A. (2020). Towards cognitive recommender systems. Algorithms, 13(8), 176. DOI: 10.3390/a13080176.
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dc.relation.referencesen31. Parush, A. (2015). Conceptual design for interactive systems: designing for performance and user experience. Morgan Kaufmann.
dc.relation.referencesen32. de Schipper, E., Feskens, R., & Keuning, J. (2021, March). Personalized and Automated Feedback in Summative Assessment Using Recommender Systems. Frontiers in Education, 6. DOI: 10.3389/feduc.2021.652070.
dc.relation.referencesen33. Veres, O., Kunanets, N., Pasichnyk, V., Veretennikova, N., Korz, R., & Leheza, A. (2019, September). Development and Operations-the Modern Paradigm of the Work of IT Project Teams. In 2019 IEEE 14th International Conference on Computer Sciences and Information Technologies (CSIT) , 3, 103–106. IEEE. DOI: 10.1109/STC-CSIT.2019.8929861.
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dc.relation.urihttps://sci-conf.com.ua/vi-mezhdunarodnaya-nauchno-prakticheskaya-konferentsiya-modern-scientific-researchachievements-innovations-and-development-prospects-21-23-noyabrya-2021-goda-berlin-germaniya-arhiv/
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dc.relation.urihttps://dialnet.unirioja.es/ejemplar/323067
dc.relation.urihttps://www.verywellmind.com/the-myers-briggs-type-indicator-2795583
dc.relation.urihttps://link.springer.com/chapter/10.1007/978-3-540-72079-9_12
dc.relation.urihttps://www.learntechlib.org/p/219036/
dc.relation.urihttps://www.omg.org/spec/UML/2.5.1/PDF
dc.relation.urihttps://blog.hootsuite.com/how-the-youtube-algorithmworks
dc.rights.holder© Національний університет “Львівська політехніка”, 2022
dc.rights.holder© Верес О., Левус Я., 2022
dc.subjectкарантин
dc.subjectметоди рекомендацій
dc.subjectметод індикатора типів особистості
dc.subjectпсихоемоційний стан людини
dc.subjectрекомендаційна система
dc.subjectquarantine
dc.subjectmethods of recommendations
dc.subjectmethod of indicator of personality types
dc.subjectpsycho-emotional state of a person
dc.subjectrecommendation system
dc.subject.udc004.8
dc.titleРекомендаційна система планування дозвілля в умовах карантину
dc.title.alternativeRecommendation system for planning leisure in quarantine conditions
dc.typeArticle

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