Eviza: A Natural Language Interface for Visual Analysis
Open accessAbstract
Natural language interfaces for visualizations have emerged as a promising new way of interacting with data and performing analytics. Many of these systems have fundamental limitations. Most return minimally interactive visualizations in response to queries and often require experts to perform modeling for a set of predicted user queries before the systems are effective. Eviza provides a natural language interface for an interactive query dialog with an existing visualization rather than starting from a blank sheet and asking closed-ended questions that return a single text answer or static visualization. The system employs a probabilistic grammar based approach with predefined rules that are dynamically updated based on the data from the visualization, as opposed to computationally intensive deep learning or knowledge based approaches.
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Most AI captioning and description systems are primarily designed to work with static images or pre-defined datasets, not with continuously updating sensor data.
“Most AI captioning and description systems are primarily designed to work with static images or pre-defined datasets, not with continuously updating sensor data that may change every few seconds [28].”
From Accessible IoT Dashboard Design with AI-Enhanced Descriptions for Visually Impaired Users (2025) · cites this paper as [28]
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References 33 · Cited by 231
Research works printed but not linked: 2
- Aurisano, J., Kumar, A., Gonzales, A., Reda, K., Leigh, J., Di Eugenio, B., and Johnson, A. Show me data? observational study of a conversational interface in visual data exploration. IEEE VIS (2015).
- Gao, T., Dontcheva, M., Adar, E., Liu, Z., and Karahalios, K. G. Datatone: Managing ambiguity in natural language interfaces for data visualization. In Proceedings of the 28th Annual ACM Symposium on User Interface Software Technology, UIST '15, ACM (New York, NY, USA, 2015), 489-500.
- Authors
- Setlur, V., Battersby, S. E., Tory, M., Gossweiler, R., & Chang, A. X.
- Affiliations
- Tableau Research, Palo Alto, CA, USA
- Tableau Software (United States) (US)
- Venue
- Proceedings of the 29th Annual Symposium on User Interface Software and Technology
- Publisher
- ACM
- Published
- 2016-10-16
- Pages
- 365-377
- OpenAlex
- W2534380090
- Cited by
- 231
- References
- 33
- Citations by year
- 2026: 35 · 2025: 23 · 2024: 32 · 2023: 21 · 2022: 30 · 2021: 25 · 2020: 30 · 2019: 16 · 2018: 13 · 2017: 5 · 2016: 1
- FWCI
- 3.99
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Symposium on User Interface Software and Technology (UIST) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Keywords
- probabilistic grammars, data analytics
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