视解剖学:一个SVG图表库,含有细粒度的语义标签
IEEE transactions on visualization and computer graphics
|November 20, 2025
概括
VISANATOMY是一个新的数据集,包含942个图表,详细标记了超过383,000个图形元素. 这个资源通过为数据可视化提供精细的语义信息来增强AI应用程序.
科学领域:
- 计算机科学 计算机科学
- 数据可视化 数据可视化
- 人工智能的人工智能
背景情况:
- 现有的图表体提供了有限的语义标签,阻碍了人工智能驱动的数据可视化研究.
- 当前数据集中的高级标签限制了它们在先进的人工智能应用中的使用.
研究的目的:
- 介绍VISANATOMY,这是一个具有多层次,细粒度的语义标签的真实世界图表的新集体.
- 提供一个全面的资源,以推进数据可视化和AI的研究.
主要方法:
- 从50多个工具中收集了942个SVG图表,涵盖40种图表类型.
- 有注释的图表,详细标记了超过383,000个图形元素,包括类型,角色,位置和视觉编码.
- 开发了多层次的层次分组和图表组件的布局信息.
主要成果:
- 与现有的图表 corpora 相比,VISANATOMY 提供了显著更丰富的语义注释.
- 通过在语义角色推断,图表分解,分类和可访问性方面的应用来证明语料库的实用性.
结论:
- VISANATOMY是人工智能驱动的数据可视化研究的宝贵资源.
- 细粒度标签使新的应用和更深入地了解图表语义成为可能.
- 进一步的研究可以增强VISANATOMY集体及其应用.
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