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Abstract

A method is described for finding correlation between a plurality of data having two kinds of numerical attributes and a true-false attribute. The method comprises the steps of: constituting a plane with two numerical attributes, dividing the plane into meshes, and counting the number of data in each mesh (also called a 'bucket') and the number of data whose true-false attribute represents true. If each mesh is assumed to be a pixel, such plane can be considered as a plane image in which the number of data corresponds to brilliance, and the number of data whose true-false attribute represents true corresponds to saturation. The method further includes the step of segmenting an admissible image which is convex along an axis of the plane according to a predetermined condition .theta. to find an area with strong correlation. If the segmented area as the admissible image satisfies the above-described condition such as the maximized support rule, the method also presents the area to the user. In addition, necessary attributes for data included in the area are also extracted from a database, as required.

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First Claim