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Currently, the Internet and social networks as a medium for the distribution of digital network content are becoming one of the most important threats to personal, public and state information security. There is a need to protect the individual, society and the state from inappropriate information. In scientific and methodological terms, the problem of protection from inappropriate information has an extremely small number of solutions. This determines the relevance of the results presented in the article, aimed at developing an intelligent system of analytical processing of digital network content to protect against inappropriate information. The article discusses the conceptual foundations of building such a system, revealing the content of the concept of inappropriate information and representing the overall architecture of the system. Models and algorithms for the functioning of the most characteristic components of the system are given, such as a distributed network scanning component, a multidimensional classification component of network information objects, a component for eliminating incompleteness and inconsistency, and a decision-making component. The article presents the results of the implementation and experimental evaluation of system components, which demonstrated the ability of the system to meet the requirements for the completeness and accuracy of detection and counteraction of unwanted information in conditions of its incompleteness and inconsistency.
Currently, the Internet and social networks as a medium for the distribution of digital network content are becoming one of the most important threats to personal, public and state information security. There is a need to protect the individual, society and the state from inappropriate information. In scientific and methodological terms, the problem of protection from inappropriate information has an extremely small number of solutions. This determines the relevance of the results presented in the article, aimed at developing an intelligent system of analytical processing of digital network content to protect against inappropriate information. The article discusses the conceptual foundations of building such a system, revealing the content of the concept of inappropriate information and representing the overall architecture of the system. Models and algorithms for the functioning of the most characteristic components of the system are given, such as a distributed network scanning component, a multidimensional classification component of network information objects, a component for eliminating incompleteness and inconsistency, and a decision-making component. The article presents the results of the implementation and experimental evaluation of system components, which demonstrated the ability of the system to meet the requirements for the completeness and accuracy of detection and counteraction of unwanted information in conditions of its incompleteness and inconsistency.
This text results from research developed in the Postgraduate Program in Education at the Tiradentes University (Unit), in partnership with the University of Aveiro, Portugal, in 2019 and 2020. The objective sought to describe how the Visualization of Data (VD) is represented in the analysis of qualitative data with the support of Qualitative Data Analysis Software (QDAS). To achieve this objective, we reached the inclusion/exclusion criteria. Seven software frequently used today, trying to understand the most frequent representations of HV in QDAS, their structuring, and how they can contribute to the phases of organisation and analysis in a scenario that can vary from small to large amounts of data. The results show that the QDAS can help the researcher visualise the qualitative data analysed with transparency through data visualisation representations that stood out in tables, charts, maps, and representations with movements. During the analysis, it was also observed that each software offers representations in different ways. The type of user/researcher interaction with the generated representations has been an exclusive phenomenon of digital technologies, which visually improves how scientific production knowledge can better circulate knowledge production.
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