Using predictive analysis of user behavior to increase the speed of reactive loading of the client part of the web application

The article is devoted to the study of methods for optimizing the client side of web applications using predictive analysis of user behavior. Modern approaches to speeding up loading, such as lazy rendering and caching, are considered, as well as their limitations related to delays in loading rare content and the need to manage the relevance of data. The main focus is on the development of a library that integrates predictive algorithms, including Markov chains and weighting with a damping factor, to adapt to changes in user preferences in real time.