Review of Data Collection and Analysis Methods in Intelligent Information Processing Systems

Ryabyy, Myroslav and Spiridonov, Anton and Korshun, Natalia and Kyrychok, Roman (2025) Review of Data Collection and Analysis Methods in Intelligent Information Processing Systems Cybersecurity Providing in Information and Telecommunication Systems 2025 (3991). pp. 611-619. ISSN 1613-0073

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Abstract

This paper examines modern methods of data collection and analysis in intelligent information processing (IIP) systems, emphasizing the growing importance of integrating non-traditional data sources into analytical frameworks. A comprehensive review of available services is conducted, highlighting their features, advantages, and limitations across various domains, including marketing, jurisprudence, medicine, and military applications. The study particularly focuses on the integration of data from messengers and public communication channels, given their increasing role in disseminating real-time information. The proposed approach combines traditional data collection services with alternative sources such as Telegram, Facebook, and YouTube, offering a more holistic and representative information environment. This integration facilitates the automated detection of patterns, trends, and anomalies, thereby enhancing decision-making processes in dynamic and data-intensive sectors. The results of experimental research confirm the viability of utilizing even unconventional information sources in analytical systems, demonstrating their effectiveness in detecting disinformation, forecasting potential threats, and automating routine analytical tasks. Furthermore, the paper introduces a conceptual model that integrates hyper-automation technologies with IIP to optimize data collection, preprocessing, and analysis. The model leverages robotic process automation (RPA) and artificial intelligence (AI)-driven classification techniques to enhance efficiency and scalability. Experimental validation of the proposed model demonstrates its potential for real-world implementation, particularly in scenarios requiring rapid adaptation to evolving information landscapes. The findings underscore the significance of hyper-automated systems in addressing contemporary challenges in data intelligence. By improving the accuracy, speed, and adaptability of information processing, such systems hold substantial promise for applications in cybersecurity, regulatory compliance, business intelligence, and public sector decision-making. The study concludes with insights into the future development of hyper-automated data processing frameworks and their role in shaping next-generation analytical capabilities.

Item Type:	Article
Uncontrolled Keywords:	intelligent information processing; hyper-automation; data analysis; monitoring systems; integration; automation; disinformation
Subjects:	Статті у базах даних > Scopus (без квартилю)
Divisions:	Факультет інформаційних технологій та математики > Кафедра інформаційної та кібернетичної безпеки ім. професора Володимира Бурячка
Depositing User:	Павло Миколайович Складанний
Date Deposited:	22 Jul 2025 08:19
Last Modified:	22 Jul 2025 08:19
URI:	https://elibrary.kubg.edu.ua/id/eprint/52543

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