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Visualization is one of the most powerful means for understanding the structure of multidimensional data. One of the most popular visualization methods is the Self-Organizing Map (SOM) that maps high dimensional data into low dimensional space while preserving the data's topological structure. While the topographical visualization can reveal the intrinsic characteristics of the data, SOM often fails...
The aim of Two-layer network visualization is to help users explore in the networks from the view of application requirement. The research abstracts applications and networks that carry them as business layer and carrier layer, which represent separately all kinds of business and service relationships among application entities and the path of information transmission in network world. A two-layer...
Stochastic neighbor embedding (SNE) aims to transform the observations in high-dimensional space into a low-dimensional space which preserves neighbor identities by minimizing the Kullback-Leibler divergence of the pairwise distributions between two spaces where Gaussian distributions are assumed. Data visualization could be improved by adopting the t-SNE where Student t distribution is used in the...
This paper presents 2-Dimensional visualization to categorize packets of network traffic into normal data pattern and attack data pattern based on the patterns resulted by a brute force attack. Two clustering methods: K-Means and Naïve Bayes methods are used to produce the data to be visualized. Experiments using ISCX and DARPA dataset were conducted. Brute force assaults on some service protocols...
DBLP (Digital Bibliography & Library Project) has the huge collection (around 3.4 million) of journal articles with its meta data, papers published in various national and international conferences, and other number of online publications in the field of computer science. Research data on DBLP increases enormously which arises many research problems in the domain of bibliography data network analysis...
Over the last decades, visual representations of data has been a commonly used medium to bolster human cognition in performance evaluation of professional athletes. However, the current approaches to these visualizations still build upon the paper based principles of initial designs with solid backgrounds. Due to this situation, same visualizations usually fail to provide explicit information about...
With the explosive growth of information in dimension and magnitude, how to understand these complex data becomes a big challenge. Visualizing data with multivariate attributes is a hot research field in the information visualization domain. This paper makes a research of multivariate data visualization, and uses various attributes mapping method in visualizing movie network data for personalized...
Large scale network has the characteristics of large number of nodes and complex structure, which makes it difficult to display in limited space. The paper proposes an expandable community division method for network visualization. The method use community detection algorithm based on network modularity to detect the network node and greedy algorithm to find the maximum modularity community. Different...
Kernel-based methods have experienced a substantial progress in the last years, tuning out an essential mechanism for data classification, clustering and pattern recognition. The effectiveness of kernel-based techniques, though, depends largely on the capability of the underlying kernel to properly embed data in the feature space associated to the kernel. However, visualizing how a kernel embeds the...
Networks in real world usually have multiple layers. Most of the current works concentrate on the single-layer network. Visualization of double-layer networks using 2.5D method is proposed in this paper to reveal the network structure and interdependent relations within network layers. A context-preserving layout method and matrix transformation is adopted to preserve node positions and reduce visual...
Visual analytic techniques are useful for studying patterns and relationships hidden in very large data sets. However, a common problem in visualizing large data sets is visual cluttering. When data get large, visual elements often get crowded, making it difficult for viewers to conduct analysis. In this paper, we present a novel method that reduces visual cluttering in spatial-temporal data visualization...
Combining distinct visual metaphors has been the mechanism adopted by several systems to enable the simultaneous visualization of multiple levels of information in a single layout. However, providing a meaningful layout while avoiding visual clutter is still a challenge. In this work we combine word clouds and a rigid-body simulation engine into an intuitive visualization tool that allows a user to...
How to draw large scale spatial interaction data clearly and quickly is a challenge in high performance data visualization research and application field. Force-Directed Edge Bundling (FDEB) helps display graph clearly with significant clutter reduction, but with high time complexity. This paper presents a parallelized FDEB on the GPU (GPU-FDEB), which reforms FDEB and achieves a balanced partitioning...
Common layout techniques for dynamic networks typically either keep node positions static as the graph changes, or operate by “tweening” optimized layouts between adjacent time slices. These techniques can be problematic because (in the first case) there is significant visual “noise” caused by unnecessary edge crossings, and (in the second case) the nodes change so much from one time slice to another...
Introduced in 2005, the Voronoi treemap algorithm is an information visualization technique for displaying hierarchical data. Voronoi treemaps use weighted, centroidal Voronoi diagrams to create a nested tessellation of convex polygons. However, despite appealing qualities, few real world examples of Voronoi treemaps exist. In this paper, we present a multi-touch tabletop application called Involv...
How to analyze the situation of the battlefield in the modern battle, and help the commander to make correct decision is the major orientation of every countriespsila researches. This paper presents a quantitative analysis and evaluation model of naval battlefield situation and gives a corresponding visual analysis model using isoline technology and potential field theory. This model can not only...
This paper presents a novel method of contour reconstruction from dexel data solving the shape anomalies for the complex geometry in virtual sculpting. Grouping and traversing processes are developed to find connectivity between dexels along every two adjacent rays. After traveling through all the rays on one slice, sub-boundaries are connected into full boundaries which are desired contours. The...
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