VisuMap Technologies
                  See the Invisible in your Data
VisuMap Applications
Creating Maps from Tables
A typical scenario

Typically, users of VisuMap will begin with a tabular dataset. As an example, the right side shows the key financial ratios of 104 US industry sections in Nov. 2003. Each industry is characterized by eight numerical values (market capitalization, price/earning ratio, etc.). VisuMap can help quickly answer questions like:
  • Which industry sections are similar to each other?
  • Is an investment portfolio sufficiently diversified?

  • How can the furture return of an investment portfolio be maximized?
US Industry Sections
US Industry Ratios

VisuMap implements a collection of dimensionality-reduction methods to represent high-dimensional datasets as low-dimensional maps.

The right side shows a map of the 104 US industry sections, as generated by VisuMap's relational perspective map algorithm. Each spot in the map represents an industry section. The area of  each spot reflects that section's price/earning ratio in that large spots represent industry sections with large price/earning ratio. A major property of this map is that two industries with similar financial ratios will be mapped to closely located positions. Thus, an investment portfolio is well diversified if its corresponding industry sections are widely distributed across the whole map.

RPM of US Industries
RPM map of US Industry Ratios

VisuMap is designed as a general purpose visualization tool for high dimensional datasets. Apart from mapping and clustering algorithms, it offers a broad palette of analysis services to explore datasets from different perspectives. The following snapshots depict some of those services (click on these maps to see larger images):


MDS (Sammon)

Self-Organizing Map

Value Diagram
Shepard Diagram

Spectrumn with Simple Value Diagram
Spectrum with Value Diagram
3D Mountain View
3D Mountain View

More sample datasets can be found here.

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