A new paper proposes an AI-driven framework to automate the digital inventory of cultural heritage and traditional knowledge for the Indonesian Digital Library of Culture (PDBI). The proposed methodology uses a five-stage process, including focused crawling, multilingual extraction, vector encoding, agentic decision-making, and idempotent publication, to overcome challenges of coverage, integrity, and completeness in manual contributions. While significantly increasing machine autonomy, the framework preserves four key human roles: curator, escalation approver, quality auditor, and guardian of meaning, ensuring ethical and cultural sensitivities are maintained. AI
IMPACT This framework could significantly improve the scale and depth of digital archives for cultural heritage globally.
RANK_REASON The cluster contains a research paper detailing a new methodology for AI-assisted digital inventory.
- alphaXiv
- arXiv
- CatalyzeX Code Finder for Papers
- Connected Papers
- DagsHub
- Gotit.pub
- Hugging Face
- Indonesian Open Digital Library of Culture
- Litmaps
- Nusantara
- Perpustakaan Digital Budaya Indonesia
- ScienceCast
- scite Smart Citations
- CatalyzeX
- Indonesian Digital Library of Culture
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