Proceedings of the VLDB Endowment · 2011 · 180 citations · 27 references
ComputingComputer ScienceAlgorithmsData StructuresNatural Language ProcessingAlgorithm AnalysisData Structure AlgorithmsAsymptotic AnalysisComplexityEdit DistanceTree AlgorithmsTree Distance MetricsWorst-case ComplexityWorst-case Optimization
We consider the classical tree edit distance between ordered labeled trees, which is defined as the minimum-cost sequence of node edit operations that transform one tree into another. The state-of-the-art solutions for the tree edit distance are not satisfactory. The main competitors in the field either have optimal worst-case complexity, but the worst case happens frequently, or they are very efficient for some tree shapes, but degenerate for others. This leads to unpredictable and often infeasible runtimes. There is no obvious way to choose between the algorithms. In this paper we present RTED, a robust tree edit distance algorithm. The asymptotic complexity of RTED is smaller or equal to the complexity of the best competitors for any input instance, i.e., RTED is both efficient and worst-case optimal. We introduce the class of LRH (Left-Right-Heavy) algorithms, which includes RTED and the fastest tree edit distance algorithms presented in literature. We prove that RTED outperforms all previously proposed LRH algorithms in terms of runtime complexity. In our experiments on synthetic and real world data we empirically evaluate our solution and compare it to the state-of-the-art.
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The Tree-to-Tree Correction Problem
Kuo‐Chung Tai · Journal of the ACM · 1979 · 863 citations · Full text
A survey on tree edit distance and related problems
Philip Bille · Theoretical Computer Science · 2005 · 753 citations
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