网络安全与数据治理2025，Vol.44Issue(3)：63-70,8.DOI:10.19358/j.issn.2097-1788.2025.03.011
面向机器学习建模的数据治理技术路径研究
Data governance technical process for machine learning modeling
李彦泽 1郭超 2孙旭明 2母东杰2
作者信息
- 1. 北京百分点科技集团股份有限公司,北京 100096
- 2. 中国电子产业工程有限公司,北京 100036
- 折叠
摘要
Abstract
With the rapid development of artificial intelligence and machine learning technologies,ensuring data quality has be-come a core factor in enhancing model performance and reliability.Particularly in the application of different types of machine learning models,how to effectively implement data governance to improve data quality,stability,and fairness remains an urgent issue to be addressed.This paper reviews the critical role of data governance in machine learning modeling and proposes a system-atic data governance framework,covering the entire process from data collection,processing,and annotation to model training.The framework aims to provide practical governance solutions to support machine learning applications.It emphasizes the adoption of targeted technical measures at different stages to ensure the effectiveness of data governance,thereby enhancing data quality and ensuring model interpretability,stability,and fairness.This research provides a theoretical foundation for the in-depth applica-tion of data governance in machine learning and offers guidance for subsequent technical practices and innovations.关键词
数据治理/机器学习/人工智能/系统框架/数据管理/模型训练Key words
data governance/machine learning/artificial intelligence/architecture/data management/model training分类
计算机与自动化引用本文复制引用
李彦泽,郭超,孙旭明,母东杰..面向机器学习建模的数据治理技术路径研究[J].网络安全与数据治理,2025,44(3):63-70,8.
