IEEE Transactions on Visualization and Computer Graphics (TVCG - InfoVis), 2009
Document Cards: A Top Trumps Visualization for Documents
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.