Comparing fuzzy data sets by means of graph matching technique

Abstract

In several applications it is necessary to compare two or more data sets. In this paper we describe a new technique to compare two data partitions of two different data sets with a quite similar structure as frequently occurs in defect detection. The comparison is obtained dividing each data set in partitions by means of a supervised fuzzy clustering algorithm and associating an undirected complete weighted graph structure to these partitions. Then, a graph matching operation returns an estimation of the level of similarity between the data sets. © Springer-Verlag Berlin Heidelberg 2003.