Nikesh Narayanan, Zayed UniversityFollow

Document Type

Book Chapter

Source of Publication

Libraries Beyond Libraries: Innovation, Inclusion and Integration

Publication Date

1-2026

Abstract

This study conceptualizes the transformative potential of RetrievalAugmented Generation (RAG) in academic research, addressing limitations of traditional search methods reliant on keyword matching, Boolean logic, and metadata analysis. RAG combines precise data retrieval with the generative capabilities of advanced AI models, synthesizing dispersed information into coherent outputs. By bridging retrieval accuracy and contextual generation, RAG offers a framework for providing researchers with comprehensive, nuanced, and up-todate insights tailored to their queries. This article explores the integration of tools like ChatGPT and LangChain to outline a RAGbased system, illustrating its potential to enhance academic discovery by harmonizing natural language processing, semantic search, and generative synthesis. It also discusses the challenges of deploying RAG systems—such as data reliability, scalability, and ethical considerations—and proposes strategies to address these obstacles. While untested, this conceptual model presents a pathway for academic libraries to redefine their role in supporting modern research needs, making academic search more intuitive, efficient, and aligned with contemporary workflows. Keywords : Academic Search, Retrieval-Augmented Generation, RAG in Academic Search, Semantic Search

ISBN

9788198930712

Publisher

ESS ESS publications

First Page

195

Last Page

209

Disciplines

Library and Information Science

Keywords

Academic Search, Retrieval-Augmented Generation, RAG in Academic Search, Semantic Search

Indexed in Scopus

no

Open Access

no

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