Research on Emergency Logistics Decision Platform Based on Knowledge Graph

Liyan He (), Juntao Li (), Meijuan Zhao () and Ruiping Yuan ()
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Liyan He: Beijing Wuzi University
Juntao Li: Beijing Wuzi University
Meijuan Zhao: Beijing Wuzi University
Ruiping Yuan: Beijing Wuzi University

A chapter in LISS 2022, 2023, pp 199-210 from Springer

Abstract: Abstract China’s geographical location is unique, and natural calamities occur frequently. In 2021, a total of 107 million people suffered from various natural disasters, and the direct economic loss reaches as high as 334.02 billion yuan. As a result, dealing with emergencies is a significant burden for the government. Improving the timeliness of emergency logistics response is a critical strategy to safeguard the national economy and people’s livelihood in times of crisis. The important data in the field of emergency logistics is unstructured or poorly structured, and there is a shortage of key information in the sector. Worse, the “data-information-knowledge” dilemma has not been sufficiently transformed. A structured semantic knowledge base is referred to as a knowledge graph. Currently, knowledge graph technology is used in a variety of industries, including medical care, e-commerce, and so on. This research provides a decision framework for emergency logistics based on knowledge graph to realize the intelligence of emergency logistics response.

Keywords: Emergency logistics; Intelligent decision; Knowledge graph (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_15

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DOI: 10.1007/978-981-99-2625-1_15

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