A Data-Driven Framework for Exploring the Spatial Distribution of Industries

Huifeng Sun ()
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Huifeng Sun: Beijing Academy Of Artificial Intelligence BAAI

A chapter in LISS 2020, 2021, pp 995-1007 from Springer

Abstract: Abstract Having a good understanding of the spatial distribution of industries, e.g., 5G, IT and New Energy, is of high importance for each country. This work thus proposes a general data-driven framework to explore and demonstrate such a distribution. First, we integrate data from different sources and build a big data store for analyzing industries. Then we develop a industry data query processing module and an industry spatial distribution analytic module based on the built data store to provide efficient queries (e.g., spatial query, keyword query and hybrid query) and intelligent data analysis (e.g., heterogeneous data fusion, industry clustering analysis, and company clustering analysis). In addition, we also develop a visualization interface to illustrate the querying and analysis results. As validated by the experiments over a real dataset, the proposed framework can well capture the spatial distribution of various industries and gives a new view of the development of industries in certain region or country.

Keywords: Industry and company; Spatial distribution of industry; Spatial clustering; Visualization (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-33-4359-7_68

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DOI: 10.1007/978-981-33-4359-7_68

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