# 利用基于案例的推理增强学术咨询

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**Published:** 2026年11月9日
**Author:** Tanat Tonguthaisri
**Source:** arXiv — cs.AI
**Language:** en-US
**HTML:** https://aiqazaqstan.com/zh/articles/enhancing-academic-advisement-with-case-based-reasoning

arXiv:2611.08572v1 通告类型：新 摘要：本研究探讨了基于案例的推理（CBR）在学术咨询领域的应用。学术咨询已被公认为高等教育的重要职能。然而，存在...

arXiv:2611.08572v1 Announce Type: new Abstract: This research involved the study of an application of Case-Based Reasoning (CBR) in the field of academic advising. Academic advisement has been recognised as an important function of higher education. However, there is a widespread desire to improve the advisement services provided by many educational institutions (e.g., colleges and universities) around the world. In the last ten years, CBR expert systems have made important contributions in many domains by applying CBR methodology to a variety of areas of human problem solving. However, to date, expert advisement systems have not been successfully applied to academic advisement, which seems to be a very appropriate domain for this technology. Academic advising is an important and time consuming task, and different tools and techniques must be used to make it an effective and efficient process. This thesis describes the design, development, and validation of a prototype case-based academic advisement recommender system that supplements the conventional advising process, and could eventually evolve to replace human academic advisors when its full potential is realised.

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*内容来自原始来源： [arXiv — cs.AI](https://arxiv.org/abs/2611.08572). 查看原文.*

**标签：** #arXiv

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