DocumentCode
446101
Title
A neural supergranph matching architecture
Author
Klinger, Stefan ; Austin, Jim
Author_Institution
Dept. of Comput. Sci., York Univ.
Volume
4
fYear
2005
fDate
July 31 2005-Aug. 4 2005
Firstpage
2453
Abstract
A neural supergraph matching architecture is introduced based on relaxation labeling and the minimum common supergraph of pairs of graphs. The system is implemented on correlation matrix memories and is efficient in constructing this supergraph. We test the effectiveness of this graphical cluster representation on two different sets of graphs
Keywords
graph theory; pattern matching; correlation matrix memories; graphical cluster representation; neural supergraph matching architecture; relaxation labeling; Approximation algorithms; Clustering algorithms; Computer architecture; Computer science; Data mining; Electronic mail; Joining processes; Labeling; Size measurement; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Conference_Location
Montreal, Que.
Print_ISBN
0-7803-9048-2
Type
conf
DOI
10.1109/IJCNN.2005.1556287
Filename
1556287
Link To Document