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