Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/33016
Title: The «smartResort» Intelligent System Development for Selecting the Sanatorium Based on Smart Metadata
Authors: Kovaleva, A. O.
Ковалева, А. О.
Baryshnikov, A. A.
Барышников, А. А.
Martirosyan, K. V.
Мартиросян, К. В.
Myasnikova, E. V.
Мясникова, Е. В.
Keywords: Data clustering;Structured data processing;Machine learning;Medical tourism;Python;Recommender system;Similarity assessment through the cosine measure
Issue Date: 2026
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Kovaleva A. O., Baryshnikov A. A., Martirosyan K. V., Myasnikova E. V. The «smartResort» Intelligent System Development for Selecting the Sanatorium Based on Smart Metadata // Proceedings of the 2026 ElCon Conference of Young Researchers on Computing and Processing, and Information Security, ElCon-CP 2026. - 2026. - pp. 224 - 227. - DOI: 10.1109/ElCon-CP69823.2026.11452174
Series/Report no.: Proceedings of the 2026 ElCon Conference of Young Researchers in Electrical Engineering, Automation and Control Systems, ElCon-EE 2026
Abstract: This paper presents the development of an intelligent recommendation system using natural language processing (NLP) and machine learning methods for personalized selection of a treatment program in a health resort institution in the Caucasian Mineral Waters, based on the analysis of medical profiles, service level and price indicators. The method includes processing structured data, ranking objects according to specified criteria and visualizing the results using clustering methods, thereby reducing the time spent on finding a suitable sanatorium by processing a large array of information. This development not only simplifies navigation in choosing a medical institution, but also increases the accuracy of recommendations by eliminating the human factor, minimizing the risks of incorrect selection of therapy, which is critical for effective rehabilitation.
URI: https://dspace.ncfu.ru/handle/123456789/33016
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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