P09-2073 semantic trees . In this context , Tree Edit Distance ( TED ) has been widely used
N13-1106 optimal edit script with the lowest tree edit distance . The approach explores both
E06-1036 should therefore be possible . 4.5 Tree edit distance The algorithm was applied using
D11-1036 δ of a parse are based on tree edit distance ( TED ) instead . TED - would
E06-1036 difficult , especially for the tree edit distance . The syntactic structure has
P09-2073 Automatic Cost Estimation for Tree Edit Distance Using Particle Swarm Optimization
D13-1044 Smith , 2010 ) develop an improved Tree Edit Distance ( TED ) model for learning tree
N13-1070 by the fact that the relative tree edit distance between translations of different
D08-1032 Kouylekov and Magnini , 2005 ) use the tree edit distance algorithms on the dependency
D11-1036 Finally , we define scores based on tree edit distance , refined to consider the distance
N13-1106 incorporated through features based on Tree Edit Distance ( TED ) . Our model is free of
N13-1106 total summed cost known as the tree edit distance . Basic edit operations include
D09-1130 represented by trees ; hence we use a " tree edit distance " for calculating d ( xi , xj
P06-1146 , we will investigate minimal tree edit distance ( Bille , 2005 ) and related
N13-1106 alignV , proper nouns alignProper 2 Tree Edit Distance Model Tree Edit Distance ( §
K15-1033 Schwartz et al. , 2011 ) , and tree edit distance ( TED ) ( Tsarfaty et al. , 2011
I05-5003 2005 ) applied both a word and tree edit distance algorithm . In this paper we
N10-1145 popular method for such tasks is Tree Edit Distance ( TED ) , which models sentence
N13-1106 Extraction as Sequence Tagging with Tree Edit Distance </title> Yao Van_Johns Hopkins
E12-1006 an evaluation measure based on tree edit distance ( TED ) which discards edit operations
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