Inheritance and protection of intangible cultural heritage in drama category based on AI human–computer interaction and digital technology

To address the challenges of insufficient content interactivity and poor user experience in the inheritance of traditional drama intangible cultural heritage in modern society, this study proposes an innovative model—the Intelligent Heritage Transmission System for Drama Culture (IHTSDC). The model uses a Higher-Order Graph Neural Network (HOGNN) combined with an attention mechanism and Low-Rank Adaptation (LoRA) algorithm to construct a dynamic relational network. This captures complex interactions among characters, scenes, and plots, enabling deep human–computer interaction. Through in-depth analysis of seven traditional dramas, including Peking Opera, Kunqu Opera, Yue Opera, Huangmei Opera, Yu Opera, Pingju, and Cantonese Opera, the results show: (1) IHTSDC excels in information extraction and content generation, with accuracy rates generally exceeding 0.80 across the traditional dramas. Notably, Peking Opera achieves an accuracy of 0.88, demonstrating IHTSDC's ability to precisely capture key elements of traditional dramas. (2) IHTSDC shows significant adaptability to different user groups, with the highest average satisfaction score reaching 4.80 (out of 5.00) among nine simulated user groups. (3) The content generated by IHTSDC aligns highly with user interests, with the highest cosine similarity reaching 0.90 and the Jaccard index consistently around 0.80, highlighting the model's high-quality output in content interaction. In summary, IHTSDC innovatively enhances the digital presentation of traditional dramas through higher-order relational modeling, dynamic feedback mechanisms, and multi-level user preference analysis, making it more aligned with the needs of modern audiences. In practical applications, IHTSDC can assist cultural institutions, art groups, and educational departments in providing personalized and high-quality traditional drama content. This strengthens the inheritance and preservation of cultural heritage, promoting the digital transformation and sustainable development of traditional culture.

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Publication Details

Journal
Discover Artificial Intelligence
Published
2025-05-22
DOI
https://doi.org/10.1007/s44163-025-00268-y
Citations
10
Primary Topic
Artificial Intelligence Applications
Type
article
Field-Weighted Citation Impact
24.81
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article

Inheritance and protection of intangible cultural heritage in drama category based on AI human–computer interaction and digital technology

Jinchang Ren
10 citations
Discover Artificial Intelligence
Artificial Intelligence Applications
24.81
article

Inheritance and protection of intangible cultural heritage in drama category based on AI human–computer interaction and digital technology

Jinchang Ren
article en
10 citations

Abstract

To address the challenges of insufficient content interactivity and poor user experience in the inheritance of traditional drama intangible cultural heritage in modern society, this study proposes an innovative model—the Intelligent Heritage Transmission System for Drama Culture (IHTSDC). The model uses a Higher-Order Graph Neural Network (HOGNN) combined with an attention mechanism and Low-Rank Adaptation (LoRA) algorithm to construct a dynamic relational network. This captures complex interactions among characters, scenes, and plots, enabling deep human–computer interaction. Through in-depth analysis of seven traditional dramas, including Peking Opera, Kunqu Opera, Yue Opera, Huangmei Opera, Yu Opera, Pingju, and Cantonese Opera, the results show: (1) IHTSDC excels in information extraction and content generation, with accuracy rates generally exceeding 0.80 across the traditional dramas. Notably, Peking Opera achieves an accuracy of 0.88, demonstrating IHTSDC's ability to precisely capture key elements of traditional dramas. (2) IHTSDC shows significant adaptability to different user groups, with the highest average satisfaction score reaching 4.80 (out of 5.00) among nine simulated user groups. (3) The content generated by IHTSDC aligns highly with user interests, with the highest cosine similarity reaching 0.90 and the Jaccard index consistently around 0.80, highlighting the model's high-quality output in content interaction. In summary, IHTSDC innovatively enhances the digital presentation of traditional dramas through higher-order relational modeling, dynamic feedback mechanisms, and multi-level user preference analysis, making it more aligned with the needs of modern audiences. In practical applications, IHTSDC can assist cultural institutions, art groups, and educational departments in providing personalized and high-quality traditional drama content. This strengthens the inheritance and preservation of cultural heritage, promoting the digital transformation and sustainable development of traditional culture.

Discover Artificial IntelligenceVol. 5(1)
Jinzhong University (CN)
Sustainable cities and communities
Openalex Percentile: Top 1%
Artificial Intelligence Applications
24.81
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Inheritance and protection of intangible cultural heritage in drama category based on AI human–computer interaction and digital technology — Jinchang Ren · Discover Artificial Intelligence (2025) | TGRS Research Map | TGRS