芬飞尔:自动化图形叠加用于金融可视化,使用知识基础的大型语言模型
IEEE transactions on visualization and computer graphics
|March 3, 2025
概括
现在可以实现对财务可视化图形叠加的自动化. 使用大型语言模型的新系统FinFlier有效地为金融叙述生成了丰富的上下文重叠.
科学领域:
- 数据可视化 数据可视化
- 金融分析 金融分析
- 自然语言处理自然语言处理.
背景情况:
- 图形重叠通过添加上下文来增强财务叙事可视化.
- 由于复杂的叙述和不清楚的设计原则,自动化这些叠加很困难.
研究的目的:
- 开发一种用于在金融可视化中生成图形重叠的自动化系统.
- 解决复杂的叙事结构和有效的重叠设计的挑战.
主要方法:
- 调查了1752个分层图表,以确定常见的重叠和叙事结构.
- 设计了FinFlier,这是一个使用知识接地大型语言模型的两阶段系统.
- 采用快速工程来进行文本数据绑定和叙事序列化以生成图形.
主要成果:
- 开发了FinFlier,这是一个用于自动化图形叠加的创新系统.
- 通过多样化的金融可视化画廊展示了系统的可行性和表现力.
- 用户研究证实了生成的分层图表的有效性和质量.
结论:
- FinFlier成功地自动化了为财务叙述创建有效的图形重叠.
- 该系统增强了财务数据和文本背景之间的联系.
- 自动覆盖可以提高财务可视化的清晰度和洞察力.
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