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Conference Paper Research on Digital Cultural Heritage Expansion Using AI Technology
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Authors
Chan-Woo Park, Hee-Kwon Kim, Jae-Ho Lee
Issue Date
2024-07
Citation
International Conference on Ubiquitous and Future Networks (ICUFN) 2024, pp.516-519
Publisher
IEEE
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/ICUFN61752.2024.10624889
Abstract
Since the early 2000s, the digital transformation of the National Museum of Korea has led to the creation of numerous digital data related to artifacts. When the initial digital cultural heritage data began to be accumulated, the focus was on ‘recording’ rather than ‘public disclosure’, so the data disclosed to the public was extremely small. In addition, unlike systematically managed cultural heritage, ‘replicated data’ in digital form is relatively unstructured in terms of creation, management, and storage. To systematize the many digital data that are piled up in a disorderly manner, a lot of manpower and cost must be invested, but there are limits to solving this with limited resources. This study proposes a standard for classifying cultural heritage data by introducing artificial intelligence technology to solve these problems, and further suggests ways to use digital data more creatively using artificial intelligence technology.
KSP Keywords
Artificial intelligence technology, Cultural heritage data, Digital cultural heritage, Digital data, Limited resources, National museum, digital transformation