The role of artificial intelligence in optimizing information retrieval systems

Abstract

The paper presents a comprehensive analysis of the application of artificial intelligence methods for the optimization of information retrieval systems. The main problems of modern IRS are investigated, particularly the inefficiency of traditional algorithms in the context of exponential growth of unstructured data volumes. Key AI methods for search improvement are systematized, including natural language processing, vector semantic search, Learning to Rank models, personalization systems, and thematic modeling. Particular attention is paid to the analysis of the balance between the power of intelligent search and ensuring information security. Promising directions for further research are identified, among which are the development of multimodal systems, the implementation of proactive search mechanisms, and the integration of dynamic ontologies.