Architecture and Implementation of an AI-Driven Digital Resource System for Art and Design Education

DOI

10.2991/978-94-6239-737-8_3How to use a DOI?

Keywords

artificial intelligence; digital resource system; art and design education; semantic analysis; recommendation system

Abstract

This paper proposes an AI-driven digital resource system for art and design education, aiming to improve the organization and utilization of multimodal educational resources. The system adopts a layered architecture, including resource management, intelligent processing, and functional application modules. By integrating artificial intelligence techniques such as automatic tagging, semantic analysis, and intelligent recommendation, heterogeneous resources are transformed into structured and semantically enriched data. The system supports efficient resource retrieval, accurate classification, and intelligent resource organization. The proposed method provides a scalable and intelligent solution for digital resource construction, contributing to enhanced efficiency and improved support for art and design education.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ling Jin
AU  - Jiufang Mei
AU  - Weijing Zhong
AU  - Yingfei Jia
PY  - 2026
DA  - 2026/08/18
TI  - Architecture and Implementation of an AI-Driven Digital Resource System for Art and Design Education
BT  - Proceedings of the 2026 5th International Conference on Art Design and Digital Technology (ADDT 2026)
PB  - Atlantis Press
SP  - 11
EP  - 17
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-737-8_3
DO  - 10.2991/978-94-6239-737-8_3
ID  - Jin2026
ER  -