By Frank van Ham
ISBN-10: 3639107004
ISBN-13: 9783639107005
Modern-day computers let us seize huge, immense datasets. in lots of instances this knowledge represents a community of connections among entities, such friendship styles in social networks, verbal exchange networks or organic pathways. totally interpreting those colossal community datasets is demanding on a couple of degrees and plenty of difficulties stay unsolved. This ebook addresses the matter from the viewpoint of knowledge visualization, which makes use of desktops to generate interactive pictures of the facts below research. It provides an summary of the cutting-edge, describes capability pitfalls and info a quantity attainable suggestions for various software parts.
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Additional info for Interactive Visualization of Large Networks: Technical challenges and practical applications
Sample text
Treemaps have been used succesfully in real-world applications to visualize the stock market [151], hard disk usage [163] and image collections [24]. 8 Treemap Applications : (a) SequoiaView uses shading and a squar- ified subdivision scheme (b) PhotoMesa uses a Quantum Treemap to show fixed sized image thumbnails. Hyperbolic Layouts Another way to increase the amount of display space available is by using hyperbolic geometry instead of traditional Euclidean geometry. Hyperbolic geometry is similar to Euclidean geometry, but without its fifth postulate, which states that if a line l does not intersect a point p there exists only one (parallel) line that intersect p and does not intersect l.
A bipartitioning algorithm, such as Fiduccia-Mattheyses [58] or spectral bipartitioning, is then applied to GL . The result of this step is then projected back (uncoarsened) into GL−1 and a limited number of iterations of the Kernighan-Lin algorithm is performed on the boundary vertices to further optimize this cut. This uncoarsening process is then repeated until we obtain a cut of the original graph. Multilevel algorithms such as [102, 18] can provide decent partitionings of graphs of tens of thousands of nodes in seconds.
Orthogonalisation : The resulting drawing is made orthogonal by converting each edge to a set of horizontal and vertical line segments. Algorithms usually try to minimize the number of bends [60]. 3. Compaction : Final vertex positions are assigned based on a specific metric. The most common metrics are minimal total edge length or drawing area. Orthogonal drawings are widely used in diagramming and schematics, making TopologyShape-Metrics based approaches very suitable for laying out UML diagrams or database schemas, for example.
Interactive Visualization of Large Networks: Technical challenges and practical applications by Frank van Ham
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