We propose a new approach to visualize social networks. Most common network visualizations rely on graph drawing. While without doubt useful, graphs suffer from limitations like cluttering and important patterns may n...
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ISBN:
(纸本)9780769541389
We propose a new approach to visualize social networks. Most common network visualizations rely on graph drawing. While without doubt useful, graphs suffer from limitations like cluttering and important patterns may not be realized especially when networks change over time. Our approach adapts pixel-oriented visualization techniques to social networks as an addition to traditional graph visualizations. The visualization is exemplified using social networks based on corporate wikis.
We have developed a pixel-oriented Treemap visualization intended for use on multiple displays with collaborating users. It visualizes the health and status of about a million devices with a Treemap layout. In this pa...
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ISBN:
(纸本)9781467347532;9781467347525
We have developed a pixel-oriented Treemap visualization intended for use on multiple displays with collaborating users. It visualizes the health and status of about a million devices with a Treemap layout. In this paper we describe how we found useful pieces of the VAST 2012 Challenge MC1dataset and discuss how users interacted with this visualization during the analysis.
visualization techniques are very useful when exploring large amount of information especially when dealing with data flow. A pixel-oriented visualization technique based on the CGR algorithm (Chaos Game Representatio...
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ISBN:
(纸本)0819439800
visualization techniques are very useful when exploring large amount of information especially when dealing with data flow. A pixel-oriented visualization technique based on the CGR algorithm (Chaos Game Representation) has been designed to help recognize type of flowing data on the fly. The CGR method -originally developed for the analysis of genomic sequences -and modified here to allow for coding bit sequences- is an algorithm that produces images where pixels dynamically display current frequencies of small groups of bits in the observed sequence. Qualitative and quantitative expressions of order, regularity, structure and complexity of sequences are perceptible from CGR images that consequently may be used for classification or identification purposes. The method has been applied to a wide range of files including texts of different languages (genomic sequences among others), images with different formats, and data or software of various origins. It is observed that CGR images are file-specific and may be consequently used as data signatures. Not only type of files can be easily identified, but subclasses of data (such as language - and eventually origin- for text), are also decipherable.
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