Finding business information by visualizing enterprise document activity
Proceedings of the International Conference on Advanced Visual Interfaces
Visualization of text streams: a survey
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Many bills: engaging citizens through visualizations of congressional legislation
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A hyperbolic tree based interface for exploring massive files
Proceedings of the 2011 Visual Information Communication - International Symposium
Word clouds for efficient document labeling
DS'11 Proceedings of the 14th international conference on Discovery science
Introduction to the Special Section on Intelligent Visual Interfaces for Text Analysis
ACM Transactions on Intelligent Systems and Technology (TIST)
TIARA: Interactive, Topic-Based Visual Text Summarization and Analysis
ACM Transactions on Intelligent Systems and Technology (TIST)
Semantic Wordification of Document Collections
Computer Graphics Forum
Visual comparison for information visualization
Information Visualization - Special issue on State of the Field and New Research Directions
Seeing beyond reading: a survey on visual text analytics
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Localised topic information extraction for summarisation using syntactic sequences
International Journal of Knowledge and Web Intelligence
Semantic-preservingword clouds by seam carving
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
Enhancing news organization for convenient retrieval and browsing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
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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.