企业高质量数据集建设运营路径研究OA
Research on the construction and operation path of enterprise-level high-quality datasets
高质量数据集已成为支撑人工智能发展和行业智能化转型的关键基础.基于此,首先分析了高质量数据集的概念与发展现状;其次针对不同类型的数据集剖析了其建设需求与核心问题;再次对企业高质量数据建设过程的关键环节和建设路径展开了研究,并针对医疗、能源、工业行业的高质量数据集建设路径进行了分析;最后探讨了高质量数据集的未来发展趋势.
High-quality datasets have become a critical foundation for supporting the development of artificial intelligence and the intelligent transformation of industries.Based on this,the study first analyzes the concept and current development status of high-quality datasets.Secondly,it examines the construction requirements and core issues of different types of datasets.Thirdly,it investigates key stages and pathways in the process of building enterprise-level high-quality datasets,analyzing the construction approaches for high-quality datasets in the healthcare,energy,and industrial sectors.Finally,it explores future development trends of high-quality datasets.
白玉真;杨靖世;袁博;王思佳;贾轩;王思源
中国信息通信研究院人工智能研究所,北京 100191中国信息通信研究院人工智能研究所,北京 100191中国信息通信研究院人工智能研究所,北京 100191中国信息通信研究院人工智能研究所,北京 100191中国信息通信研究院人工智能研究所,北京 100191中国信息通信研究院人工智能研究所,北京 100191
管理科学
高质量数据集人工智能数据工程
high-quality datasetsAIdata engineering
《信息通信技术与政策》 2026 (5)
10-15,6
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