Publication: TASM: Top-k Approximate Subtree Matching
TASM: Top-k Approximate Subtree Matching
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Augsten, N., Böhlen, M., Barbosa, D., & Palpanas, T. (2010). TASM: Top-k Approximate Subtree Matching. ACM Trans. Database Syst., Proceedings of the 26th International Conference on Data Engineering, ICDE 2010, March 1-6, 2010, Long Beach, California, USA, 353–364. https://doi.org/10.1109/ICDE.2010.5447905
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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 memory-efficient and scalable TASM algorithm. We p
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- Augsten, N
- Barbosa, D
- Palpanas, T
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Augsten, N., Böhlen, M., Barbosa, D., & Palpanas, T. (2010). TASM: Top-k Approximate Subtree Matching. ACM Trans. Database Syst., Proceedings of the 26th International Conference on Data Engineering, ICDE 2010, March 1-6, 2010, Long Beach, California, USA, 353–364. https://doi.org/10.1109/ICDE.2010.5447905
