This article examines the theoretical and practical aspects of processing information on variable-structured multi-parameter objects. The dynamic structure of such objects, their multidimensional parametric description, heterogeneous data sources, dependence on the time factor, and hierarchical organization are analyzed as their main characteristics. Using tax administration as an example, mathematical models aimed at data integration, normalization, and the identification of risk indicators are proposed. In addition, an architectural approach has been developed for adaptive structural-parametric modeling, multi-level information processing, and decision support. The research results contribute to improving information quality and enhancing monitoring efficiency in complex management systems.
Gulchexra Jamalova (Sun,) studied this question.