Real-time Visualization of Streaming Text with Force-Based Dynamic System, Jamal Alsakran, Yang Chen, Dongning Luo, Ye Zhao, Jing Yang, Wenwen Dou, and Shixia Liu, IEEE Computer Graphics and Applications (CG&A), 32(1), pages 34-45, 2012, IEEE (PDF)(Bibtex).
STREAMIT: Dynamic visualization and interactive exploration of text streams, Jamal Alsakran, Yang Chen, Ye Zhao, Jing Yang, and Dongning Luo. Proceedings of IEEE Pacific Visualization Symposium, March, 2011, IEEE. (PDF) (PPT)
An interactive visualization system, STREAMIT, enables users to explore text streams on-the-fly without prior knowledge of the data. It incorporates incoming documents from a continuous source into existing visualization context with automatic grouping and separation based on document similarities. STREAMIT supports interactive exploration with good scalability: First, keyword importance is adjustable on-the-fly for preferred clustering effects from varying interests. Second, topic modeling is used to represent the documents with higher level semantic meanings. Third, document clusters are generated to promote better understanding. The system performance is optimized to achieve instantaneous animated visualization even for a very large data collection. STREAMIT provides a powerful user interface for in-depth data analysis. Case studies are presented to demonstrate the effectiveness of STREAMIT.
Use STREAMIT in a VAST appliation:
Supporting Effective Common Ground Construction in Asynchronous Collaborative Visual Analytics, Yang Chen, Jamal Alsakran, Scott Barlowe, Jing Yang, and Ye Zhao, IEEE Conference on Visual Analytics Science and Technology, pages 101, VisWeek, October, 2011, IEEE. (PDF)(Bibtex)
Example1. New York Times news stream
Example2. US NSF IIS award stream
Vast application: A Collaborative Visual Analytics System