Abstract
War archive is a quintessential big data issue about national history and military data security in urgent need of exploitation. Knowledge graph is one of the core technologies of knowledge engineering in the era of big data. With the ability of deep knowledge reasoning and progressively expanding cognition, knowledge graph has become a key technology for the construction and application in the field of military big data. Most of the existing knowledge graph is general knowledge graph for general fields, but there is no mature method of knowledge graph construction and application for the military archival big data. Taking the archival data of the War to Resist U.S. Aggression and Aid Korea as an example, this paper, based on the special needs for military archive fields, explores the construction path of knowledge graph from the aspects of knowledge modeling, knowledge extraction, knowledge fusion and knowledge management. At the same time, the application of knowledge retrieval, archive resource linking, knowledge Q & A, knowledge recommendation and other scenarios are explored.
The authors extend their appreciation to the Young Foundation of National Social Science in China (Grand Nos: 2019-SKJJ-C-064, 19CTQ033).
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Yongqin, H., Xushan, C., Anlian, Y., Shuo, P. (2023). Research on Application of Knowledge Graph in War Archive Based on Big Data. In: Tian, Y., Ma, T., Jiang, Q., Liu, Q., Khan, M.K. (eds) Big Data and Security. ICBDS 2022. Communications in Computer and Information Science, vol 1796. Springer, Singapore. https://doi.org/10.1007/978-981-99-3300-6_17
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DOI: https://doi.org/10.1007/978-981-99-3300-6_17
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