Articulate: a Semi-automated System for Translating Natural Language Queries into Meaningful Visualizations

Researchers: Abeer Alsaiari, Abhinav Kumar, Andrew Johnson, Jason Leigh, Jillian Aurisano, Joe Borowicz, Luc Renambot, Vijayraj Mahida, Yiwen Sun, Barbara DiEugenio

Funding: NSF IIS-1445751: EAGER

While many visualization tools exist that offer sophisticated functions for charting complex data, they still expect users to possess a high degree of expertise in wielding the tools to create an effective visualization. Articulate is a semi-automated visual analytic system that is guided by a conversational user interface to allow users to verbally describe and then manipulate what they want to see. Natural language processing and machine learning methods are used to translate the imprecise sentences into explicit expressions, and then a heuristic graph generation algorithm is applied to create a suitable visualization. The goal is to relieve the user of the burden of having to learn a complex user-interface in order to craft a visualization.


Date: March 1, 2009 - Ongoing
Screenshot of Articulate system - Y. Sun, EVL

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