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Bayesian graph edit distance
2000
IEEE Transactions on Pattern Analysis and Machine Intelligence
AbstractÐThis paper describes a novel framework for comparing and matching corrupted relational graphs. The paper develops the idea of edit-distance originally introduced for graph-matching by Sanfeliu and Fu [1] . We show how the Levenshtein distance can be used to model the probability distribution for structural errors in the graph-matching problem. This probability distribution is used to locate matches using MAP label updates. We compare the resulting graph-matching algorithm with that
doi:10.1109/34.862201
fatcat:67g6xlon35gcbc63bndp4ayxfq