数据增强用于可视化设计知识库的数据增强
IEEE transactions on visualization and computer graphics
|November 20, 2025
概括
本研究引入了数据增强,以改善可视化知识库. 新的方法产生和标记更多的图表对,增强计算推理和图表推准确性.
科学领域:
- 计算机科学 计算机科学
- 数据可视化 数据可视化
背景情况:
- 可视化知识库有助于设计空间中的计算推理.
- 目前的系统使用从有限的图表对数据中学习的特征权重,缺乏全面的权衡评估.
研究的目的:
- 为了提高可视化知识库的覆盖范围和准确性.
- 开发数据增强技术,用于生成和标记图表对.
- 为了扩大标签努力,学习更新的功能权重.
主要方法:
- 数据增强技术用于通过设计变换生成新的图表对,并识别低估的特征.
- 对各种方法进行比较,以扩大对图表对进行注释的标签努力.
- 在Draco知识库背景下进行评估.
主要成果:
- 一个扩展的集体,有成千上万的新图表对.
- 在功能覆盖方面取得了明显的改进.
- 增强图表推性能. 提高图表推性能.
结论:
- 数据增强显著扩展可视化知识库训练数据.
- 提出的方法提高了学习特征权重的准确性和覆盖率.
- 这项工作增强了可视化设计中的计算推理和推能力.
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