The myth of the double-blind review?: author identification using only citations
ACM SIGKDD Explorations Newsletter
Content-Based Image Retrieval Based on a Fuzzy Approach
IEEE Transactions on Knowledge and Data Engineering
A new fuzzy relaxation algorithm for image enhancement
International Journal of Knowledge-based and Intelligent Engineering Systems
Understanding the schema matching problem
ACS'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 7
A quadratic programming based cluster correspondence projection algorithm for fast point matching
Computer Vision and Image Understanding
Similarity-Based Retrieval With Structure-Sensitive Sparse Binary Distributed Representations
Computational Intelligence
Efficient globally optimal matching of anatomical trees of the liver
EG VCBM'10 Proceedings of the 2nd Eurographics conference on Visual Computing for Biology and Medicine
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Graphs are very powerful and widely used representational tools in computer applications. We present a relaxation approach to (sub)graph matching based on a fuzzy assignment matrix. The algorithm has a computational complexity of O(n2m2) where n and m are the number of nodes in the two graphs being matched, and can perform both exact and inexact matching. To illustrate the performance of the algorithm, we summarize the results obtained for more than 12 000 pairs of graphs of varying types (weighted graphs, attributed graphs, and noisy graphs). We also compare our results with those obtained using the graduated assignment algorithm