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While data visualization is not new, I am proposing that higher-level math be used to create dynamic relationships which will assist in knowledge discovery. Here are several website examples to illustrate the concept:

  • We Feel Fine–(Jonathan Harris) A visual mapping of all emotional statements in the blogosphere
  • Universe–(Jonathan Harris) A visual mapping of news stories.
  • Live Plasma–Relating musicians and movies through visualization
  • Wiki Mind Map–New initiative into mapping Wikipedia using the opensource MindMap software.
  • CNet
  • Discover The Network

Mathematics to define relationships

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Tags and categories can be used to define what topics are related, which statistical analysis (Link Analysis, data mining, and information theory) can be used to define the strength of the relationship.

  • Del.icious
  • Link Analysis
  • Data Mining/Knowledge Discovery
  • Social Networking Theory
  • Information Theory

Detailed Math

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Information Theory

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A fundamental measure in Information Theory is entropy. Entropy is a measure of uncertainty in a communication system, but it can be used as a weighting value of a random process. Given a node x, calculate an entropy value of each branch and then normalize each value. The resulting value can be used to weight the length/thickness of the relationship.

Example Images

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In order to better visualize the concept, I created several graphic examples. My thought is you could navigate the map by clicking and dragging or by entering a search term. Each node in the map represents a wiki or blog page which opens in a new window.

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File:Tech Tree.jpg

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File:Region Tree.jpg