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Visual Data Mining Concepts

Best practices on how to use simple flash animations in combination with prezi Path and Frames - to achieve a strong narrative.

Nermien Hanna

on 21 April 2010

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Transcript of Visual Data Mining Concepts

Advantages 1. In VDE, user can easily deal with highly inhomogeneous and noisy data Easy to deal with 2. Insightful VDE is intuitive and requires no understanding of complex mathematical or statistical algorithms or parameters. 3. Fast and confident Weather example
VDE usually allows a faster data exploration and often provides better results By Nermien Hanna Visual DATA and Surprise your audience with
unexpected changes
in ratio, optical illusions and
hidden details. "Visual presentation of the data close to the mental model" ...and don't forget:
there is a lot to
explore in VDE.. so be on the
lookout for
new CONCEPTS Visual Data Mining Advantages Paradigm of Visual Data Exploration (VDE) Classifications of Visual Data Mining Techniques VDE Conclusion Allow human to get insight into the data Draw conclusions Directly interact with the data Outline PARADIGM of VDE Overview first 3 Steps: The user identifies interesting patterns in the
data and focuses on one or more of them.
Step 1: Step 2: Zoom and filter Focus on the interesting subsets.
Step 3: Details-on-demand To further explore the interesting subsets, the user needs a drill-sown capability in order to observe the details about the data. Techniques can be classified into: The data to be visualized The visualization technique The interaction and distortion technique Interaction and Destoration techniques 2D data, such as geographical maps
Data type to be Multi-dimensional data - Parallel Coordinate Data Type to be Visualization Techniques Dense Pixle Displays: Recursive Pattern Dense Pixel Displays: Circle segments Interactive Zooming: Table Lenses visualized visualized Conclusion The problem Has high potential and many Future work will involove Tight integration of visualization of exploration of large data sets studies! MINING ... techniques with traditional applications techniques Visual Data Mining
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