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  4. Vol 9, Issue 2, 2026

Research on the Construction of Intelligent Q&A System for University Scientific Research Management Based on Retrieval-Augmented Generation

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DOI: 10.23977/jaip.2026.090204 | Downloads: 0 | Views: 63

Author(s)

Yang Lei 1

Affiliation(s)

1 Yunnan Open University, Kunming, China

Corresponding Author

Yang Lei

ABSTRACT

With the deepening of digital transformation in university scientific research management, traditional manual consultation services can no longer meet the growing demand for research management inquiries. Taking the research qualification review scenario at Yunnan Open University as a case study, this paper designs and implements an intelligent question-answering system based on Retrieval-Augmented Generation (RAG) technology. The system innovatively adopts a four-layer hybrid architecture integrating a Drools rule engine, vector retrieval, large language models, and knowledge graphs. By deploying open-source large models locally and constructing a multi-source knowledge base with vector and graph databases, the system effectively addresses the hallucination problem and insufficient interpretability of LLMs in the compliance review scenario of research management. This study provides a replicable, low-cost technical path and practical reference for the intelligent transformation of university research management services.

KEYWORDS

Retrieval-Augmented Generation; Large Language Model; Research Management; Intelligent Question-Answering System; Educational Digital Transformation

CITE THIS PAPER

Yang Lei. Research on the Construction of Intelligent Q&A System for University Scientific Research Management Based on Retrieval-Augmented Generation. Journal of Artificial Intelligence Practice (2026). Vol. 9, No. 2, 34-40. DOI: http://dx.doi.org/10.23977/jaip.2026.090203.

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