大数据2025，Vol.11Issue(6)：47-56,10.DOI:10.11959/j.issn.2096-0271.2025088
构建企业级人工智能高质量数据集:方法与路径
Building high-quality datasets for enterprise-level artificial intelligence:methods and pathways
摘要
Abstract
Currently,the artificial intelligence(AI)datasets in our country face challenges,including the lack of quality evaluation methods and an unclear capability-building system.This article reviews the composition and classification of AI datasets and combines structured data quality assessment to propose a set of evaluation methods for AI dataset quality.Based on industry practices,it distills a high-quality AI data engineering system,summarizes the pathways for enterprises to develop capability building,and provides policy recommendations for constructing high-quality datasets in our country.关键词
人工智能数据集/数据质量评估/人工智能数据工程Key words
artificial intelligence datasets/data quality assessment/AI data engineering分类
计算机与自动化引用本文复制引用
姜春宇,白玉真,刘渊,王超伦..构建企业级人工智能高质量数据集:方法与路径[J].大数据,2025,11(6):47-56,10.
