Year: 2022
Type: preprint
Abstract: We develop NL2INTERFACE to explore the potential of generating usable interactive multi-visualization interfaces from natural language queries. With NL2INTERFACE, users can directly write natural language queries to automatically generate a fully interactive multi-visualization interface without any extra effort of learning a tool or programming language. Further, users can interact with the interfaces to easily transform the data and quickly see the results in the visualizations.
Source: arXiv (Cornell University)
Authors: Chen, Yiru, Li, Ryan, Mac, Austin, Xie, Tianbao, Yu, Tao, Wu, Eugene
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
Awards: Collaborative Research: CNS CORE: Medium: A Unified Prefetch Framework for Approximation Tolerant Interactive Applications, CAREER: Visual Database Interfaces, III: Small: Bringing database query optimization to data intensive applications, Elements: Open-Source Cyberinfrastructure as a Decision Engine for Socioeconomic Disaster Risk (DESDR), SI2-SSE: Improving Scikit-Learn Usability and Automation
OpenAlex ID: W4296567516