Research on Knowledge Graph Platform of Logistics Industry Based on Big Data

Fan Yang, Juntao Li, Ruiping Yuan (), Fan Wang and Huanli Zhao
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Fan Yang: Beijing Wuzi University, Beijing Key Laboratory of Intelligent Logistics Systems
Juntao Li: Beijing Wuzi University, Beijing Key Laboratory of Intelligent Logistics Systems
Ruiping Yuan: Beijing Wuzi University, Beijing Key Laboratory of Intelligent Logistics Systems
Fan Wang: Beijing Wuzi University, Beijing Key Laboratory of Intelligent Logistics Systems
Huanli Zhao: Beijing Wuzi University, Beijing Key Laboratory of Intelligent Logistics Systems

A chapter in LISS 2022, 2023, pp 305-313 from Springer

Abstract: Abstract China's logistics industry started late, with the rapid development of the national economy, China's logistics industry maintains a fast growth rate, and the data generated is growing explosively. Data and knowledge are the basis for the deep integration of new-generation information technology and intelligent manufacturing. How to efficiently and accurately analyze multi-source and heterogeneous data in various systems of the logistics industry is a major problem faced by people in the logistics industry. The knowledge graph is a new type of accurate knowledge representation method, which has gradually begun to land in medical, financial, and other industries. For the characteristics of the logistics industry, this paper conducts special research on five aspects, including knowledge acquisition, knowledge processing, knowledge graphing, knowledge application, and knowledge reasoning. It aims to promote the application of the knowledge graph platform in the logistics industry and provide decision-making support for auxiliary event-driven and industry-important events.

Keywords: Logistics industry; Knowledge graph; Big data (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-99-2625-1_23

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DOI: 10.1007/978-981-99-2625-1_23

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