DEVELOPMENT OF AN AI-BASED INTELLIGENT RECOMMENDATION SYSTEM FOR DIGITAL LIBRARY PLATFORMS

This scientific paper investigates the development and performance evaluation of an artificial intelligence-based intelligent recommendation system designed specifically for digital library platforms. Traditional library search engines often rely on basic keyword matching, which significantly limits user engagement and fails to deliver personalized content. To address this limitation, this study proposes a hybrid recommendation model that effectively integrates collaborative filtering and content-based filtering algorithms. The practical experiment conducted at the technical institute demonstrated that the AI-driven system substantially reduces content retrieval time, enhances user interaction metrics, and achieves exceptional recommendation precision compared to conventional methods.