Research on campus question answering system supported by retrieval-augmented generation technology
To solve the problem of obtaining effective information from the vast amount of campus information for teachers and students, an intelligent campus question answering (QA) system based on RAG was designed. An approach that integrates large language models and domain knowledge for QA system construct...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2024-11-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2024259/ |
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| Summary: | To solve the problem of obtaining effective information from the vast amount of campus information for teachers and students, an intelligent campus question answering (QA) system based on RAG was designed. An approach that integrates large language models and domain knowledge for QA system construction was proposed, relying on the campus’s <italic>Everything You Need to Know</italic> project, and using campus information such as procedural guides, frequently asked questions, and normative documents as an external data corpus. A campus knowledge database was constructed, with the RAG Infinity database. To improve the retrieval efficiency of domain knowledge and the accuracy of answers, the prompt approach was proposed. Using RAG for campus QA, the system provides users various service information in an interactive manner, which helps to solve common campus issues, simplify the consultation process for teachers and students, and alleviate the burden on campus management, and enrich campus knowledge resources. |
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| ISSN: | 1000-436X |