Print Email Facebook Twitter Using knowledge graphs and deep learning algorithms to enhance digital cultural heritage management Title Using knowledge graphs and deep learning algorithms to enhance digital cultural heritage management Author Huang, Y. (TU Delft Design Conceptualization and Communication; Northwestern Polytechnical University) Yu, S. Suihuai (Northwestern Polytechnical University) Chu, J. Jianjie (Northwestern Polytechnical University) Fan, H. Hao (Zhejiang University) Du, B. Bin (Northwestern Polytechnical University; Shanghai Jiao Tong University) Date 2023 Abstract Cultural heritage management poses significant challenges for museums due to fragmented data, limited intelligent frameworks, and insufficient applications. In response, a digital cultural heritage management approach based on knowledge graphs and deep learning algorithms is proposed to address the above challenges. A joint entity-relation triple extraction model is proposed to automatically identify entities and relations from fragmented data for knowledge graph construction. Additionally, a knowledge completion model is presented to predict missing information and improve knowledge graph completeness. Comparative simulations have been conducted to demonstrate the effectiveness and accuracy of the proposed approach for both the knowledge extraction model and the knowledge completion model. The efficacy of the knowledge graph application is corroborated through a case study utilizing ceramic data from the Palace Museum in China. This method may benefit users since it provides automated, interconnected, visually appealing, and easily accessible information about cultural heritage. Subject Chinese ceramicsCultural heritageDeep learningKnowledge completionKnowledge extractionKnowledge graph To reference this document use: http://resolver.tudelft.nl/uuid:cb8f6ddf-484c-41ae-b614-b69b83ca04cd DOI https://doi.org/10.1186/s40494-023-01042-y ISSN 2050-7445 Source Heritage Science, 11 (1) Part of collection Institutional Repository Document type journal article Rights © 2023 Y. Huang, S. Suihuai Yu, J. Jianjie Chu, H. Hao Fan, B. Bin Du Files PDF s40494_023_01042_y.pdf 16.2 MB Close viewer /islandora/object/uuid:cb8f6ddf-484c-41ae-b614-b69b83ca04cd/datastream/OBJ/view