基于本地部署RAG的课程选择学术咨询系统
A Locally Deployed RAG-Based Academic Advising System for Course Selection
AI总结：
提出一种本地部署的RAG学术咨询系统，利用大语言模型和结构化课程大纲检索，以隐私保护方式支持课程选择、先修课程理解和个性化学习规划。
摘要：
基于课程之间先修关系的正确课程顺序对于学生全面发展知识和技能至关重要。然而，学生孤立地制定这一顺序时，常常因认知局限和信息过载而困惑。同时，教育机构由于教育资源有限，在提供关于正确顺序的充分学术建议方面遇到困难。为解决这些挑战，我们提出一种基于课程大纲信息的本地部署RAG学术咨询系统。通过将大语言模型与结构化课程大纲数据的检索相结合，该系统旨在以隐私保护的方式支持课程选择、先修课程理解和个性化学习规划。
英文摘要：
The correct sequence of courses in the curriculum based on prerequisites between courses is of great importance for students to develop their knowledge and skills holistically. However, students crafting this sequence in isolation frequently struggle with recognition limitations and information overload that leads to confusion. Simultaneously, education institutions encounter difficulties in providing adequate academic advice for the correct sequence due to limited education resources. To address these challenges, we propose a locally deployed RAG-based academic advising system grounded in syllabus information. By combining large language models with retrieval from structured syllabus data, the system is designed to support course selection, prerequisite understanding, and personalized study planning in a privacy-preserving manner.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
