PREDICATE DATA ANALYSIS FOR BUILDING A LOGICAL NETWORK-BASED SYSTEM FOR OPTIMAL VACATION SPOT SELECTION

Abstract

Relevance. The rapid development of information technologies significantly increases the volume of data that needs to be processed. Therefore, the development and application of new mathematical methods for analyzing data of various types are of great importance. To address this issue, the language of finite predicates was chosen for systematic data analysis, as it allows for the decomposition of multi-place relations. Objective. From a theoretical perspective, predicate analysis facilitates the formalization of information represented in both digital and natural language formats. Alternatively, an appropriate decomposition of a multidimensional relation into a composition of binary relations can enhance information processing efficiency when determining an optimal solution by enabling parallel processing of binary relations corresponding to the nodes of a logical network. The objective of this study is to investigate and decompose the problem domain to construct a mathematical model in the form of a logical network. Methodology. The approach to constructing a logical network by decomposing complex multi-place predicates into a combination of simpler binary predicates enables the development of an information system that not only performs analysis but also synthesis and comparison tasks. This is achieved by applying linear logical transformations at each step of the network’s operation. Scientific novelty. A detailed systematic analysis of a specific subject area allows for the construction of a mathematical model of a particular selection problem. Thus, the complex system for selecting a vacation spot was represented as a logical model consisting of a composition of nine binary predicates. In the article, they are presented in the form of bipartite graphs and corresponding formulas. The developed mathematical model includes a predicate dependent on ten variables and serves as the basis for effective analysis and comparison of options. Conclusions. The practical significance of this work lies in the subject area analysis through data decomposition during the construction of a mathematical model for a logical network. This approach simplifies many-tomany relationships into one-to-one relationships, thereby facilitating faster information processing. Ultimately, the constructed logical network effectively assists in finding the optimal vacation type for a client based on specified parameters, as well as solving analysis, synthesis, and comparison tasks.