Algorithm of adaptation of electronic document management system based on machine learning technology

The topical problem in the development of electronic document management systems (EDMS) is their adaptation and personalization to the individual characteristics of the user. This article discusses the issue of development of an adaptation algorithm using machine learning methods for solving the problem of structural-parametric synthesis of EDMS. In the framework of the presented algorithm, the approaches to the formalization of workflow processes, ways to adapt the interface to the user parameters using artificial neural networks and a comprehensive assessment of the system’s adaptability are considered. The scientific novelty of the approach consists in the algorithmic and software development for automation of the data collection, analysis and interface adaptation through the use and integration of neural networks in the information system. The application of machine learning methods for the formation and adaptation of EDMS interface allows you to automate the process of personalizing it to the user’s individual characteristics, increase the system’s flexibility and provide the best user experience at the first interaction with EDMS based on the intelligent analysis of data about other users. The main scientific results obtained in the article include: formalized criteria for adapting EDMS; algorithm for designing and adapting EDMS; and development of software for adapting EDMS, including a trained neural network and API.