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.
Comparing Fuzzy Data Sets by Means of Graph Matching Technique / Acciani, Giuseppe; Fornarelli, G.; Liturri, L.. - 2714:(2003), pp. 367-374. (Intervento presentato al convegno Joint International Conference ICANN/ICONIP 2003 tenutosi a Istanbul, Turkey nel June 26–29, 2003) [10.1007/3-540-44989-2_44].
Comparing Fuzzy Data Sets by Means of Graph Matching Technique
ACCIANI, Giuseppe;
2003-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
