Toward Interface Defaults for Vague Modifiers in Natural Language Interfaces for Visual Analysis
IEEE Vis - Oct 20-25, 2019
Natural language interfaces for data visualizations tools are growing in importance, but little research has been done on how a system should respond to questions that contain vague modifiers like ``high'' and ``expensive.'' This paper makes a first step toward design guidelines for this problem, based on existing research from cognitive linguistics and the results of a new empirical study with 274 crowdsourcing participants. A comparison of four bar chart-based views finds that highlighting the top items according to distribution-sensitive values is preferred in most cases and is a good starting point as a design guideline.