法人和其他组织统一社会信用代码数据国民经济行业数据质量提升方法研究  

Research on the Method of Improving the Quality of Unifi ed Social Credit Identifi er Data and Industrial Data of National Economic Activities of Legal Entities and Other Organizations

作　　者：赵捷 袁辉 邓祥武 宫政 司琳华 金江 ZHAO Jie;YUAN Hui;DENG Xiang-wu;GONG Zheng;SI Lin-hua;JIN Jiang(China Organization Data Service)

机构地区：[1]全国组织机构统一社会信用代码数据服务中心

出　　处：《中国标准化》2024年第5期66-71,共6页China Standardization

基　　金：国家市场监督管理总局科技计划项目“基于深度学习技术的法人和其他组织国民经济行业分类机器判定研究”(项目编号:2020MK185)资助。

摘　　要：在国民经济行业分析过程中,法人和其他组织的统一社会信用代码数据起着至关重要的作用,其不仅是产业和统计分析工作的基础,数据质量的优劣更会直接影响到分析结果的准确性。本文以提升数据质量为出发点,首先对数据质量问题进行精准鉴别,其次构建混合型自动化行业分类模型,并提出了数据质量持续提升的常态化标准化流程机制。这种策略在提供持续、迭代的改进机制的同时,也为国民经济行业的数据分析提供了更为坚实和可靠的数据保障。In the process of national economic industry analysis,the data of unified social credit code of legal entities and other organizations plays a vital role.It is the basis of industrial and statistical analysis,the quality of which also directly affect the accuracy of analysis results.Taking data quality improvement as the starting point,this paper first accurately identifies data quality problems,then builds a hybrid automation industrial classification model,and proposes a normalized standardized process mechanism for continuous improvement of data quality.This strategy not only provides a continuous and iterative improvement mechanism,but also provides a more solid and reliable data guarantee for the data analysis of the national economic activities.

关 键 词：统一社会信用代码 国民经济 自动化行业分类模型 数据质量提升 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] F203[自动化与计算机技术—计算机科学与技术] F124[经济管理—国民经济]