VIRTUAL CURATION METHODS FOR ORGANIZING LARGE-SCALE INTERNATIONAL DIGITAL ART EXHIBITIONS
DOI:
https://doi.org/10.29121/shodhkosh.v7.i4s.2026.7495Keywords:
Virtual Curation, Digital Art Exhibitions, AI-driven Classification, Semantic Organization, Cross-cultural Adaptability, Machine LearningAbstract [English]
International exhibition of digital art and the rise in worldwide connectivity of cultures have required new strategies of managing large-scale exhibitions. Conventional curation approaches are severely constrained by handling thousands of arts pieces representing different cultural backgrounds, necessitating manual sorting, thematic sorting by hand, and being not very scalable. This study suggests an all-encompassing virtual curation solution that uses artificial intelligence, machine learning, and semantic technologies to plan and automate the process of organizing international digital art exhibitions. The suggested multi-layer system combines the data retrieval on world repositories, AI-based classification and clustering, automated theme generation, and the customized user navigation in virtual exhibition areas. Using convoluted neural networks to extract visual features, natural language processing to extract metadata and graph of knowledge to perform semantic linking, the system attains more accuracy in curation relevance than traditional approaches. The results of experimental evaluation with a wide range of 15,000 digital artworks representing 47 countries show that there are considerable gains in the quality of curation, measures of diversity, and user interactions. The framework is 92.4% curation relevance accurate, 0.847 diversity index and 87.3% user satisfaction score and also exhibitions of 100 to 10,000 or more works of art can be scaled. The performance benchmarks demonstrate that it has 89.7% efficiency improvement in time compared to manual curation and greater cross-cultural adaptability. The system has been able to roll out three international virtual exhibitions and this proves that it can be applied practically. This study forms a scalable, smart model on how to democratize entry to digital art in the planet, maintaining cultural authenticity and artistic integrity.
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Copyright (c) 2026 Fabiola M. Dhanraj, Mahesh Kurulekar, Sakshi Pahariya, Akash Kumar Bhagat, Jaskirat Singh, Anitha M, Dr. Balkrishna K. Patil
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