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| Construction of Knowledge Graph of Industry Chain Based on Natural Language Processing |
| Mao Ruibin1,2, Zhu Jing2, Li Aiwen2, Zhou Yiwen2, Pan Binqiang2, Yue Lin3 |
1.Center for Studies of Information Resources, Wuhan University, Wuhan 430072
2.Shenzhen Securities Information Co., Ltd, Shenzhen 518022
3.Department of Management and Economics, Tianjin University, Tianjin 300110 |
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Abstract Industry chain knowledge graphs are widely used in the financial field, but most of the current studies are based on single-industry knowledge graphs or industrial competitive intelligence services, and these have not organically combined the industry chain and knowledge graph. From the perspective of the application, this paper examines the construction method of the industry chain knowledge graph. First, the construction process and ontology database are proposed. Based on the domain language model, the financial domain text processing methods such as knowledge classification, extraction, and fusion are realized, massive domain texts are extracted and integrated, and the industrial chain knowledge graph is successfully constructed. The industry chain knowledge graph system constructed according to the method herein covers 78 industrial chains and 7629 subdivided industries, which is applied to many critical financial activities such as investment and financing, supervision, and industrial planning.
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Received: 02 March 2020
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