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[Question] The construction of cultural knowledge base in digital library is in progress with the development of information technology. However, traditional cultural knowledge bases are facing the problems of high participation of manual operation and monotonous data source. This paper combines knowledge graph, a frontier technology of artificial intelligence, to explore a new method of building high‐quality, automated cultural knowledge base. [Method] Using the experimental method, we selected the knowledge of the Hundred Schools of Thought in ancient China. Because these knowledges are clearly interrelated, it is suitable to construct the knowledge graph of them. The knowledge graph can provide experience for the construction of other cultural knowledge bases. [Conclusion] At present, this paper has preliminarily completed the experimental design of the knowledge graph of the Hundred Schools of Thought, and provided the flowchart of the construction of cultural domain knowledge graph.

Based on the panel data of Jinzhou, Panjin, Songyuan, Daqing, Yangzhou, Dongying and other 20 oil and gas resource-based cities from 2010 to 2018, combined with DEA-SBM model and Malmquist-Luenberger index, using DEA-SOLVERPro 5.0 and MaxDEA software. This paper evaluates the green growth efficiency of oil and gas resource-based cities from static and dynamic perspectives.The results show that the average static efficiency of green growth of the main oil and gas resource-based cities in China does not reach 1, there is efficiency loss, and it does not reach Pareto optimum.The static efficiency of green growth of the eastern oil and gas resource-based cities is higher than that of other regions, which is in line with the law of the Environmental Kuznets Curve. The environment has been improved. More than half of the oil and gas resource-based cities have a dynamic efficiency value of green growth greater than 1, and the development trend of green growth is better.

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