DocumentCode
1528411
Title
Visualizing text data sets
Author
Booker, Andrew ; Condliff, Michelle ; Greaves, Mark ; Holt, Fred B. ; Kao, Anne ; Pierce, Daniel J. ; Poteet, Stephen ; Wu, Y.-J.J.
Author_Institution
The Boeing Co., Seattle, WA, USA
Volume
1
Issue
4
fYear
1999
Firstpage
26
Lastpage
35
Abstract
The authors present a visualization methodology which provides users with a way to alter perspectives and interpret visualization so that they can quickly identify trends, outliers, and possible clusters while tuning for a particular context. The technology developed for text mining is called Trust, or Text Representation Using Subspace Transformation. Trust provides an analysis environment that can supply meaningful representations of text documents; it also supports the functional ability to visually present a collection of documents in a meaningful context that allows for user insight and textual content. Contrary to other similar technologies, Trust applies a novel analysis ability that allows different subspaces to generate views, providing content information for the basis of the visualization and allowing an analyst to specify subspaces for it based on content
Keywords
data mining; data visualisation; text analysis; Text Representation Using Subspace Transformation; Trust; analysis ability; analysis environment; content information; outliers; subspaces; text data set visualization; text documents; text mining; textual content; user insight; visualization methodology; Consumer electronics; Data analysis; Data engineering; Data mining; Data visualization; Engines; Histograms; Information analysis; Scattering; Text mining;
fLanguage
English
Journal_Title
Computing in Science & Engineering
Publisher
ieee
ISSN
1521-9615
Type
jour
DOI
10.1109/5992.774838
Filename
774838
Link To Document