Paper Info
Title
Document cards: a top trumps visualization for documents.
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
DOI
Venue
2009
10.1109/TVCG.2009.139
IEEE Trans. Vis. Comput. Graph.
Keywords
Field
DocType
image color histogram,automatic document structure extraction,document cards,semi-semantic image weighting,large document collection,key semantic,important key term,ieee infovis publication,advanced text mining approach,top trumps visualization,key term,non-empty image class,histograms,operating systems,data visualisation,displays,text mining,data mining,display devices,color histogram,document structure,pipelines,search engines,visualization
Histogram,Data visualization,Heuristic,Weighting,Information retrieval,Color histogram,Visualization,Computer science,Document Structure Description,Display device
Journal
Volume
Issue
ISSN
15
6
1077-2626
Citations 
PageRank 
References 
41
1.45
27
Authors
6
Name
Order
Citations
PageRank
Hendrik Strobelt138721.65
Daniela Oelke222513.18
Christian Rohrdantz320513.86
Andreas Stoffel422911.66
Daniel A. Keim577041141.60
Oliver Deussen62852205.16