Useful properties of Semantic Depth of Field for better F+C visualization
VISSYM '02 Proceedings of the symposium on Data Visualisation 2002
Designing Pixel-Oriented Visualization Techniques: Theory and Applications
IEEE Transactions on Visualization and Computer Graphics
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Root Polar Layout of Internet Address Data for Security Administration
VIZSEC '05 Proceedings of the IEEE Workshops on Visualization for Computer Security
Visualization of Geo-spatial Point Sets via Global Shape Transformation and Local Pixel Placement
IEEE Transactions on Visualization and Computer Graphics
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
The utility of linguistic rules in opinion mining
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Literature Fingerprinting: A New Method for Visual Literary Analysis
VAST '07 Proceedings of the 2007 IEEE Symposium on Visual Analytics Science and Technology
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Scalable pixel based visual data exploration
VIEW'06 Proceedings of the 1st first visual information expert conference on Pixelization paradigm
Visual Thinking: for Design
Information Visualization
A simple dense pixel visualization for mobile sensor data mining
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
Advanced visual analytics methods for literature analysis
LaTeCH '12 Proceedings of the 6th Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities
Fingerprint matrices: uncovering the dynamics of social networks in prose literature
EuroVis '13 Proceedings of the 15th Eurographics Conference on Visualization
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Pixel-based visualizations have become popular, because they are capable of displaying large amounts of data and at the same time provide many details. However, pixel-based visualizations are only effective if the data set is not sparse and the data distribution not random. Single pixels - no matter if they are in an empty area or in the middle of a large area of differently colored pixels - are perceptually difficult to discern and may therefore easily be missed. Furthermore, trends and interesting passages may be camouflaged in the sea of details. In this paper we compare different approaches for visual boosting in pixel-based visualizations. Several boosting techniques such as halos, background coloring, distortion, and hatching are discussed and assessed with respect to their effectiveness in boosting single pixels, trends, and interesting passages. Application examples from three different domains (document analysis, genome analysis, and geospatial analysis) show the general applicability of the techniques and the derived guidelines.