The use of graphs to model the dependencies of factors in the scope of the concept of information reliability
Year: 2026
Type: article
Abstract: Context and relevance. Knowledge of the composition of information trustworthiness dependencies is necessary for organizing information processing based on information trustworthiness (TI), including the creation of automated systems with intelligent processing. The known verbal and analytical descriptions of TI dependencies are incomplete and inconsistent. Objective. To identify the dependence of TI on its quality components in order to ensure the synthesis of methodological and software tools for the development of automatic TI assessment tools. Hypothesis. Generalization and systematization of data on the composition of particular formulations of TI dependencies will lead to a single sufficient model of TI dependencies on its factors. Methods and materials. The study uses a model of the scope of the concept of TI, previously obtained by processing the provisions of the scattered theory of information trustworthiness. The methods of graph theory, situational management and hermeneutics are used to form a model of the dependencies of the information content from the scope of the concept. Representation models and empirical algorithms for manipulating the graph of TI dependences have been developed. Results. The main result of the work is a model of the dependence of TI on the components of information quality. The resulting procedure and dependency model of the TI make it possible to overcome semantic dispersion and inconsistency in the descriptions of the TI. Conclusions. The resulting model of TI dependencies shows the relative relationship of particular descriptions of TI, their place in TI, and explains their semantic dispersion. The TI dependency model contains fundamental descriptions of dependencies and is a means of ensuring a purposeful process of searching and forming meaningful descriptions of patterns (analytical formulas).
Source: Modelling and Data Analysis
Author: D.V. Kubrakov
Institution: Moscow Aviation Institute
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7214769158