Stanislav Trubin

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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(More)
Traditional application of Voronoi diagrams for space partitioning creates Voronoi regions, with areas determined by the generators' relative locations and weights. Especially in the area of information space (re)construction, however, there is a need for inverse solutions; i.e., finding weights that result in regions with predefined areas. In this thesis,(More)
We define the spatial constraints and objective function for weight-proportional partitioning of information spaces. We evaluate existing methods in light of these definitions and find that none performs as desired. We then formulate an alternative approach based on an adaptive version of the multiplicatively weighted Voronoi diagram; i.e., the diagram' s(More)
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 that minimizes area deviations. We apply the method to(More)
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