Sociomap Visualization

In this work we study algorithms for visualization of sociomaps. We focus on surface-fitting method which converts bitmap picture into a sequence of closed spline curves. For curve-fitting, we describe tracing algorithm that for a given level of height in a smooth surface finds a contour as a closed Bézier curve. Further we describe algorithm that draws hierarchy of clusters into a 2D plane. We first create a skeleton of the cluster analysis which we then project into a plane using curve-fitting method. We describe methods of interpolation of surface based on inverse distances weights and also we present a linear interpolation based on Delanauy triangulation. We apply these methods on sociomappig analysis. Sociomapping is a data-mining method for visualization of relations among objects as well as analyzing statistical data. The result of sociomapping analysis is an easy-to-read picture - a sociomap. We explain cluster analysis for model of a sociomap and also we describe statistical test based on fuzzy approach