Affiliations: School of Economics and Management, Handan University, Handan, China
Correspondence:
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Corresponding author: Jianwei Song, School of Economics and Management, Handan University, Handan, China. E-mail: jianwei_song@outlook.com.
Abstract: With the continuous advancement of the global industrialization process, industrial cultural heritage has gradually attracted the attention of all parties, but its protection and excavation still face multiple challenges. The purpose of this study is to explore the conservation and mining strategies of global industrial cultural heritage based on big data. Through a comprehensive analysis of the value and status quo of industrial cultural heritage, this study integrates multi-source data and constructs a big data processing and analysis model by using the questionnaire method. The research results show that big data has significant application potential and practical value in the protection of industrial cultural heritage, and can provide more accurate and personalized protection strategies. Based on the data analysis, this study further proposes a series of practical conservation and excavation strategies to provide strong support for the sustainable development of industrial cultural heritage. This comprehensive analysis and practical recommendations are expected to advance scientific research and policy implementation in this area.
Keywords: Industrial cultural heritage, big data, protection policy, data mining, sustainable development
