Work

Innovation and Development of Intangible Cultural Heritage Protection and Inheritance Under the Background of Artificial Intelligence

Year: 2025

Type: article

Abstract: Intangible Cultural Heritage (ICH) represents the customers, behaviors, and expressions that have been handed down through the generations, including folklore, performing arts, rituals, languages, and craftsmanship. Unlike tangible heritage, including objects and monuments, ICH is vulnerable to destruction due to globalization, urbanization, and generational gaps. Traditional methods of preservation, such as manual documentation and oral transmission, struggle to adapt to the digital era, leading to the loss of valuable cultural knowledge. Artificial Intelligence (AI) has become a revolutionary instrument for ICH preservation, offering solutions for digital preservation, restoration, and interactive dissemination. To address these issues, this research proposes a Galactic Swarm Optimized Graph Neural Network (GSO-GNN) for ICH’s improved inheritance and protection. The proposed approach begins with comprehensive ICH preservation of data. A pre-processing phase, including data cleaning and noise reduction, ensures the accuracy and consistency of the dataset and then feature extraction was conducted using Principal Component Analysis (PCA). The GNN is then employed to map complex relationships between cultural elements, preserving their contextual significance. To enhance efficiency, GSO is integrated to refine feature selection, improve model accuracy, and optimize computational resources. The findings show that the proposed method outperforms other techniques in terms of the [Formula: see text]1-score (98%), recall (98.48%), accuracy (99%), and precision (98%). Furthermore, AI-driven dissemination significantly enhances accessibility and engagement for global audiences, contributing to cultural sustainability and protection. By efficiently modeling complex cultural relationships and optimizing computational performance, the GSO-GNN platform offers a practical and scalable way to preserve digital heritage.

Source: International Journal of High Speed Electronics and Systems

DOI: 10.1142/s0129156425500132

Authors: Weihong Xu, Ban Wu

Institution: Wuhan Business University

Language: English

Topic: Cultural Heritage Management and Preservation

Subfield: Archeology

Field: Arts and Humanities

Domain: Social Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funder: Ministry of Education