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TASM: Top-k Approximate Subtree Matching
2010
2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)
We consider the Top-k Approximate Subtree Matching (TASM) problem: finding the k best matches of a small query tree, e.g., a DBLP article with 15 nodes, in a large document tree, e.g., DBLP with 26M nodes, using the canonical tree edit distance as a similarity measure between subtrees. Evaluating the tree edit distance for large XML trees is difficult: the best known algorithms have cubic runtime and quadratic space complexity, and, thus, do not scale. Our solution is TASMpostorder, a
doi:10.1109/icde.2010.5447905
dblp:conf/icde/AugstenBBP10
fatcat:b6roqaf6ubd7bkj5dljekvu43i