DocumentCode :
3416059
Title :
Visual evaluation of text features for document summarization and analysis
Author :
Oelke, Daniela ; Bak, Peter ; Keim, Daniel A. ; Last, Mark ; Danon, Guy
Author_Institution :
Univ. of Konstanz, Konstanz
fYear :
2008
fDate :
19-24 Oct. 2008
Firstpage :
75
Lastpage :
82
Abstract :
Thanks to the Web-related and other advanced technologies, textual information is increasingly being stored in digital form and posted online. Automatic methods to analyze such textual information are becoming inevitable. Many of those methods are based on quantitative text features. Analysts face the challenge to choose the most appropriate features for their tasks. This requires effective approaches for evaluation and feature-engineering.
Keywords :
data visualisation; text analysis; Web-related textual information; document analysis; document summarization; quantitative text feature; text feature visual evaluation; text visualization techniques; Algorithm design and analysis; Feature extraction; Feedback loop; Information analysis; Iterative algorithms; Iterative methods; Performance analysis; Text analysis; Text mining; Visualization; I.5.2 [Pattern Recognition]: Design Methodology—Feature evaluation and selection; I.7.5 [Document and Text Processing]: Document Capture—Document Analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Analytics Science and Technology, 2008. VAST '08. IEEE Symposium on
Conference_Location :
Columbus, OH
Print_ISBN :
978-1-4244-2935-6
Type :
conf
DOI :
10.1109/VAST.2008.4677359
Filename :
4677359
Link To Document :
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