| Literature DB >> 19834183 |
Hendrik Strobelt1, Daniela Oelke, Christian Rohrdantz, Andreas Stoffel, Daniel A Keim, Oliver Deussen.
Abstract
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.Year: 2009 PMID: 19834183 DOI: 10.1109/TVCG.2009.139
Source DB: PubMed Journal: IEEE Trans Vis Comput Graph ISSN: 1077-2626 Impact factor: 4.579