Knowledge Graph-Based Design Method for the Integration of Red Cultural and Multi-Ethnic Cultural Elements

DOI

10.2991/978-94-6239-737-8_5How to use a DOI?

Keywords

Knowledge Graph; Cultural Integration; Red Culture; Multi-Ethnic Culture; Art Design; Semantic Reasoning

Abstract

This paper proposes a knowledge graph-based design method for integrating red cultural and multi-ethnic cultural elements in art design. First, multi-source cultural data are collected and annotated, and a structured knowledge graph is constructed through BERT-based named entity recognition and relation extraction to represent entities and their semantic relationships. Then, a graph-driven semantic reasoning mechanism is developed to support the association and integration of cultural elements for design tasks. Furthermore, a knowledge graph-based design support approach provides intelligent recommendations and improves design efficiency. Experimental results demonstrate that the proposed method achieves higher performance in knowledge extraction and enhances design quality and efficiency. The proposed approach provides a systematic and intelligent solution for cultural integration and offers new insights for AI-assisted cultural design.

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  - Yingfei Jia
AU  - Weijing Zhong
AU  - Ling Jin
AU  - Jiufang Mei
PY  - 2026
DA  - 2026/08/18
TI  - Knowledge Graph-Based Design Method for the Integration of Red Cultural and Multi-Ethnic Cultural Elements
BT  - Proceedings of the 2026 5th International Conference on Art Design and Digital Technology (ADDT 2026)
PB  - Atlantis Press
SP  - 25
EP  - 31
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-737-8_5
DO  - 10.2991/978-94-6239-737-8_5
ID  - Jia2026
ER  -