知识图
计算机科学
知识管理
重新使用
数据科学
人工智能
工程类
废物管理
作者
Yuhu Shang,Yimeng Ren,Hao Peng,Yue Wang,Gang Wang,Zhong Cheng Li,Yangzhao Yang,Yangyang Li
标识
DOI:10.1109/icmlc58545.2023.10327989
摘要
As a result of the development of a new generation of artificial intelligence and carbon-neutral technologies, traditional industries are undergoing dramatic transformations. The exploration of industrial intelligence is still in its nascent stages, particularly lacking technical approaches to distill experiential knowledge from heterogeneous data sources originating from various origins. Knowledge Graphs (KG), as cutting-edge artificial intelligence technologies, can enable knowledge management and reuse while condensing valuable knowledge. As a result, fully utilizing KG's potential in the industrial field is critical to the realization of autonomous sensing, cognition, and the evolution of next-generation intelligent manufacturing systems. This paper starts with an overview of the current state of industrial knowledge graph development and shows how to construct an industrial knowledge graph (IKG). Following that, we provide a thorough and in-depth review of various industrial scenarios supported by knowledge graphs. Furthermore, this paper identifies the current challenges confronting industrial applications and proposes future research directions for IKG. It is hoped that this research will draw the attention of more researchers to the knowledge graph-based smart manufacturing paradigm and benefit their work.
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