Evolution of Search From Lexical Methods to Semantic Technologies With AI-Driven Vector Models

The article is devoted to the evolution of search technologies, which is caused by the development oftechnological processes. Because of this, a transition was made from simple lexical methods to modernsemantic technologies based on vector models controlled by artificial intelligence. Initially, search enginesrelied on keyword selection, which, despite its simplicity, often did not allow them to assess the contextualsignificance of queries. The main purpose of the work is to consider the historical process of development ofsearch technologies, as well as to study the role of artificial intelligence, which is used in vector models.The article provides an overview of various search models, starting with logical, vector spatial, andending with modern semantic search technologies based on artificial intelligence. It also describes how theseachievements have improved the accuracy and relevance of search results.The information presented in the framework of the work will be useful for consideration by otherscientific authors, as well as programmers and employees working in the field of information retrieval, machinelearning and artificial intelligence. Due to the fact that it gives an idea of the evolution of search engines,thereby provides a basis for understanding future trends in the development of search technologies.