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STREAMIT: Dynamic Visualization and Interactive Exploration of Text Streams

By Jamal Alsakran, Yang Chen, Ye Zhao, Dongning Luo and Jing Yang


Text streams demand an effective, interactive, and on-the-fly method to explore the dynamic and massive data sets, and meanwhile extract valuable information for visual analysis. In this paper, we propose such an interactive visualization system that enables users to explore streaming-in text documents without prior knowledge of the data. The system can constantly incorporate incoming documents from a continuous source into existing visualization context, which is “physically ” achieved by minimizing a potential energy defined from similarities between documents. Unlike most existing methods, our system uses dynamic keyword vectors to incorporate newly-introduced keywords from data streams

Topics: Furthermore, we propose a special keyword
Year: 2013
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