提升数据价值:质量控制在数据标注过程的应用与优化

Increasing Data Value:Application and Optimization of Quality Control in Data Annotation Process

数据质量是数据分析和应用的基石,而良好的质量控制方法是连接数据质量与数据分析应用效能的桥梁与纽带。为研究质量控制在标注过程中的应用与优化方法,以提高流程标准化水平,本文从质量控制的角度出发,分析当前数据标注过程中数据质量可能存在的问题,通过评估体系建设、调整组织结构框架、项目制度建设、实施半自动化标注流程等方法应对当前质量控制存在的风险与挑战。最后,对数据标注过程中质量控制未来可能的发展态势进行总结,为提高团队应对数据质量风险的能力、支持业务决策提供支撑。

Data quality is the cornerstone of data analysis and application,with robust quality control methodologies serving as the bridge between the data quality and the efficiency of data analysis and application.To explore the application and optimization methods of quality control in the annotation process for enhancing the level of standardization,this paper analyzes the potential issues of data quality in the data annotation process from the perspective of quality control.Through establishing assessment system,adjusting organizational framework,conducting project system construction,and implementing semi-automated annotation process,the current risks and challenges in quality control can be addressed.Finally,the paper summarizes the possible future development trends of quality control of the data annotation process,providing support to improve the teams’capability to deal with data quality risks and facilitate business decision-making.