Information Space Regionalization Using Adaptive Multiplicatively Weighted Voronoi Diagrams

Authors:
Rene Reitsma;Stanislav Trubin;Saurabh Sethia
Affiliations:
Oregon State University;Oregon State University;Oregon State University
Venue:
IV '04 Proceedings of the Information Visualisation, Eighth International Conference
Year:
2004

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Abstract

In an attempt to regionalize and visualize regions of information space, we offer a method for regionalization based on predetermined area relationships. This problem can be conceptualized as an inverse multiplicatively weighted Voronoi diagram. To compute such a diagram, we offer an adaptive algorithm. Initial testing indicates good results and quick convergence.