Paper Details

Name: Karunakar N. , Nagesh R.
Country: India

Year: 2026
Volume: Volume-13, Issue-2, Year-2026 (July-December)
Page Number: 6-16
DOI: https://doi.org/10.5281/zenodo.21888883

ABSTRACT
Digital libraries are rapidly evolving from conventional repositories into intelligent knowledge environments capable of providing contextual, personalized, and semantically enriched information services. The integration of Artificial Intelligence (AI), Large Language Models (LLMs), Semantic Web technologies, and Knowledge Graphs offers significant opportunities to improve information retrieval and intelligent knowledge discovery. This study proposes a hybrid framework that integrates AI and LLM-based natural-language processing with semantic knowledge representation, ontologies, metadata, and Knowledge Graphs. The proposed framework combines conventional keyword retrieval, semantic search, and AI-based contextual processing to improve the accuracy and relevance of retrieved information. It further incorporates intelligent question answering, summarization, recommendation, and personalized user interaction. The methodology adopts a systematic and analytical research design using scholarly literature, digital library resources, metadata, and suitable datasets. The framework is evaluated using retrieval accuracy, relevance, usability, user satisfaction, and knowledge-discovery measures, including precision, recall, and F1-score. The study also addresses major challenges associated with AI-enabled digital libraries, including hallucination, reliability, algorithmic bias, privacy, data security, copyright, explainability, and human oversight. The proposed framework contributes to Library and Information Science by providing an integrated technological model for next-generation digital libraries. It demonstrates how the convergence of AI, LLMs, and Semantic Web technologies can support more intelligent, context-aware, personalized, and knowledge-oriented information discovery while emphasizing responsible and trustworthy AI adoption.

Keywords: Artificial Intelligence, Large Language Models, Digital Libraries, Semantic Web, Knowledge Graphs, Intelligent Information Retrieval, Knowledge Discovery, Generative AI