Data Science and Engineering (Apr 2023)

A Survey of Advanced Information Fusion System: from Model-Driven to Knowledge-Enabled

  • Di Zhu,
  • Hailian Yin,
  • Yidan Xu,
  • Jiaqi Wu,
  • Bowen Zhang,
  • Yaqi Cheng,
  • Zhanzuo Yin,
  • Ziqiang Yu,
  • Hao Wen,
  • Bohan Li

DOI
https://doi.org/10.1007/s41019-023-00209-8
Journal volume & issue
Vol. 8, no. 2
pp. 85 – 97

Abstract

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Abstract Advanced knowledge engineering (KE), represented by knowledge graph (KG), drives the development of various fields and engineering technologies and provides various knowledge fusion and knowledge empowerment interfaces. At the same time, advanced system engineering (SE) takes model-based system engineering (MBSE) as the core to realize formal modeling and process analysis of the whole system. The two complement each other and are the key technologies for the transition from 2.0 to 3.0 in the era of artificial intelligence and the transition from perceptual intelligence to cognitive intelligence. This survey summarizes an advanced information fusion system, from model-driven to knowledge-enabled. Firstly, the concept, representative methods, key technologies and application fields of model-driven system engineering are introduced. Then, it introduces the concept of knowledge-driven knowledge engineering, summarizes the architecture and construction methods of advanced knowledge engineering and summarizes the application fields. Finally, the combination of advanced information fusion systems, development opportunities and challenges are discussed.

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