Research Article
Research on the Traceability and Aggregation System of Intelligent Q&A for University Smart Services
@INPROCEEDINGS{10.4108/eai.18-12-2025.2365279, author={Dong Yang and Qiurui Sun}, title={Research on the Traceability and Aggregation System of Intelligent Q\&A for University Smart Services}, proceedings={Proceedings of the 13th International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2025, 18-21 December 2025, Chengdu, China}, publisher={EAI}, proceedings_a={IIKI}, year={2026}, month={6}, keywords={smart campus intelligent Q\&A prompt engineering information traceability knowledge aggregation}, doi={10.4108/eai.18-12-2025.2365279} }- Dong Yang
Qiurui Sun
Year: 2026
Research on the Traceability and Aggregation System of Intelligent Q&A for University Smart Services
IIKI
EAI
DOI: 10.4108/eai.18-12-2025.2365279
Abstract
Universities have accumulated extensive structured data resources across various smart campus systems. However, the current development of intelligent Q&A services faces common challenges, including knowledge fragmentation, lack of traceability, and inefficient aggregation. This paper proposes an intelligent Q&A system based on a traceable knowledge graph and prompt enhancement technology. Each knowledge item is bound to an individual page URL, while knowledge collections are configured with aggregation page URLs. By constructing a scenario-adaptive prompt framework, the system guides large language models (LLMs) to accurately output corresponding page URLs in response to user queries. Results from data simulation experiments demonstrate that the system exhibits high information accuracy and practical application value.
