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Issue No.06 - November/December (2009 vol.15)
pp: 1145-1152
Daniela Oelke , University of Konstanz
Christian Rohrdantz , University of Konstanz
Andreas Stoffel , University of Konstanz
Daniel A. Keim , University of Konstanz
Oliver Deussen , University of Konstanz
Finding suitable, less space consuming views for a document’s main content is crucial to provide convenient access to large document collections on display devices of different size. We present a novel compact visualization which represents the document’s key semantic as a mixture of images and important key terms, similar to cards in a top trumps game. The key terms are extracted using an advanced text mining approach based on a fully automatic document structure extraction. The images and their captions are extracted using a graphical heuristic and the captions are used for a semi-semantic image weighting. Furthermore, we use the image color histogram for classification and show at least one representative from each non-empty image class. The approach is demonstrated for the IEEE InfoVis publications of a complete year. The method can easily be applied to other publication collections and sets of documents which contain images.
document visualization, visual summary, content extraction, document collection browsing
Daniela Oelke, Christian Rohrdantz, Andreas Stoffel, Daniel A. Keim, Oliver Deussen, "Document Cards: A Top Trumps Visualization for Documents", IEEE Transactions on Visualization & Computer Graphics, vol.15, no. 6, pp. 1145-1152, November/December 2009, doi:10.1109/TVCG.2009.139
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