Visual Evaluation of Text Features for Document Summarization and Analysis

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OELKE, Daniela, Peter BAK, Daniel A. KEIM, Mark LAST, Guy DANON, 2008. Visual Evaluation of Text Features for Document Summarization and Analysis. 2008 IEEE Symposium on Visual Analytics Science and Technology (VAST). Columbus, OH, USA, 19. Okt 2008 - 24. Okt 2008. In: 2008 IEEE Symposium on Visual Analytics Science and Technology. 2008 IEEE Symposium on Visual Analytics Science and Technology (VAST). Columbus, OH, USA, 19. Okt 2008 - 24. Okt 2008. IEEE, pp. 75-82. ISBN 978-1-4244-2935-6

@inproceedings{Oelke2008-10Visua-5899, title={Visual Evaluation of Text Features for Document Summarization and Analysis}, year={2008}, doi={10.1109/VAST.2008.4677359}, isbn={978-1-4244-2935-6}, publisher={IEEE}, booktitle={2008 IEEE Symposium on Visual Analytics Science and Technology}, pages={75--82}, author={Oelke, Daniela and Bak, Peter and Keim, Daniel A. and Last, Mark and Danon, Guy} }

Bak, Peter application/pdf Visual Evaluation of Text Features for Document Summarization and Analysis Danon, Guy deposit-license eng 2008-10 First publ. as paper in: IEEE Symposium on Visual Analytics and Technology (VAST 2008), October 21 - 23, Columbus, Ohio, USA 2011-03-24T16:01:15Z Last, Mark Oelke, Daniela Bak, Peter Last, Mark 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. In this paper we suggest an approach to visually evaluate textanalysis features as part of an interactive feedback loop between evaluation and feature engineering. We apply documentfingerprinting for visualizing text features as an integral part of the analytic process. Consequently, analysts are able to access interim results of the applied automatic methods and alter their properties to achieve better results.<br />We implement and evaluate the methodology on two different tasks, namely opinion analysis and document summarization and show that our iterative method leads to improved performance. 2011-03-24T16:01:15Z Keim, Daniel A. Keim, Daniel A. Oelke, Daniela Danon, Guy

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