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ArthurNote: An AI-Driven Note-taking Platform Eliminating Repetitive Tasks
- 1 School of Computer Science & Technology, Soochow University, Suzhou 215000, China
- 2 International School of Information Science & Engineering, Dalian University of Technology, Dalian 116024, China
* Author to whom correspondence should be addressed.
Abstract
The note-taking procedure performs a significant role in education and business, offering a simple methodology to schedule routines, emphasize important parts, and review previous events. However, it is tedious and superfluous for students to record common knowledge that already exists in the public domain. Existing online noting platforms can not satisfy our requirements. This paper introduces an innovative approach to enhancing the note-taking experience by integrating large language models (LLM) and cutting-edge development technology within our AI-aided note-taking platform. The development of the new platform is based on a methodology of front-end and back-end separation, and it is empowered by the NoSQL cloud database and online LLM service to increase its scaling ability. With LLM’s help in completing, the redundant efforts of users have been eliminated to a large degree.
Keywords
note-taking LLM AI education cloud database efficiency
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Cite this article
Gao,C.;Shi,Z. (2025). ArthurNote: An AI-Driven Note-taking Platform Eliminating Repetitive Tasks. Applied and Computational Engineering,132,36-42.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 2nd International Conference on Machine Learning and Automation
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