Comparing fuzzy data sets by means of graph matching technique

Authors:
Giuseppe Acciani;Girolamo Fornarelli;Luciano Liturri
Affiliations:
Electro-technology and Electronics Department, Politecnico di Bari, Bari, Italy;Electro-technology and Electronics Department, Politecnico di Bari, Bari, Italy;Electro-technology and Electronics Department, Politecnico di Bari, Bari, Italy
Venue:
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Year:
2003

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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.