信息通信技术与政策2026，Vol.52Issue(5)：22-31,10.DOI:10.12267/j.issn.2096-5931.2026.05.004
基于多模态融合与AI辅助的高质量数据集构建方法与实践
A methodological framework for high-quality dataset construction based on multimodal fusion and AI assistance
王栋 1杨华锋 1刘威辰 1李康 1刘敬谦 1刘世伟1
作者信息
- 1. 中国电信集团有限公司,北京 100033
- 折叠
摘要
Abstract
Building high-quality datasets for AI applications often faces four practical challenges:unclear alignment with business goals,fragmented implementation,limited technical infrastructure,and excessive annotation costs,this paper presents a methodology that addresses these issues through a three-layer framework-demand mapping,intelligent governance,and value realization-implemented on China Telecom's Knowledge Service Platform.The methodology has been validated in high-end equipment manufacturing and consumer goods industries,cutting dataset construction time,offering a practical pathway for enterprise data asset development in the era of data marketization.关键词
高质量数据集/多模态融合/AI辅助标注/数据资产管理Key words
high-quality dataset/multimodal fusion/AI-assisted annotation/data asset management分类
信息技术与安全科学引用本文复制引用
王栋,杨华锋,刘威辰,李康,刘敬谦,刘世伟..基于多模态融合与AI辅助的高质量数据集构建方法与实践[J].信息通信技术与政策,2026,52(5):22-31,10.
