IEEE Trans Vis Comput Graph. 2018 Jan;24(1):309-318. doi: 10.1109/TVCG.2017.2744684. Epub 2017 Aug 29.
Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.
交互式可视数据分析最具成效的情况是，用户能够专注于回答他们对数据提出的问题，而不是专注于如何操作分析工具的界面。一种可行的方法是通过可视化的自然语言界面来吸引用户与他们的数据进行互动对话。与其他交互范例相比，这些界面具有更具表现力和更易访问的潜力。我们探讨了如何将语言语用学原理应用于可视分析对话的流程中，将自然语言作为输入方式。我们评估了我们的系统 Evizeon 中语用学支持的有效性，并提出了用于可视分析工具的对话界面的设计注意事项。
