Abstract
With the multi-source intelligence data grow exponentially, traditional methods can barely satisfy the requirement, which means to organize and understand the tremendous military knowledge. So, this research project aims to develop unified, highly connected military knowledge graph to integrate information. Using front-end interaction technology, supporting learning function based on inference, error-correcting and marking, this graph can continuously modify the logic model and improve the intelligence of itself, so the knowledge will be solid in our department. By doing this, we can reduce our dependence on the experience of special experts, and moreover, provide platform for developing data-driven general battle system in recent years.
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Hu, R. (2020). U.S. Air Force Target Knowledge Graph Construction Based on Multi-source Intelligence Analysis. In: Huang, C., Chan, YW., Yen, N. (eds) Data Processing Techniques and Applications for Cyber-Physical Systems (DPTA 2019). Advances in Intelligent Systems and Computing, vol 1088. Springer, Singapore. https://doi.org/10.1007/978-981-15-1468-5_41
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DOI: https://doi.org/10.1007/978-981-15-1468-5_41
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