P14-3008 individual sentences applying parse tree kernels to paragraphs . We build a set
P06-1104 improves the speed . Finally , the parse tree kernel requires exact match between
P06-1104 - tion . They suggest that the parse tree kernel can effectively explore the syntactic
P06-1104 entity kernel and a convolution parse tree kernel . To our knowledge , convolution
P06-1104 entity kernel and a convolution parse tree kernel . Our study demonstrates that
P06-1104 two entities . ( 2 ) Convolution Parse Tree Kernel : A convolution kernel aims to
P06-1104 approximate matching mechanisms in the parse tree kernel calculation . Finally , it is
P10-1090 parts ) of the input objects . The parse tree kernel ( Collins and Duffy , 2002 )
P10-1073 sub-trees of further offspring . The parse tree kernel counts the number of common sub-trees
P06-1104 sub-trees of further offspring . The parse tree kernel counts the number of common sub-trees
P07-1026 2001 ) proposed the following parse tree kernel to calculate the dot product
P06-1104 2001 ) proposed the following parse tree kernel to calculate the dot product
D09-1073 2001 ) proposed the following parse tree kernel to calculate the dot product
E06-1015 paper , Section 2 describes the parse tree kernels and our fast algo - rithm . Section
P06-1104 which can be well captured by the parse tree kernel . In addition , we find that
P06-1104 entity-related features and a convolution parse tree kernel that models syntactic information
P09-2092 parse tree kernel and dependency parse tree kernel outperforms all others by 5.7
N06-1037 convolution tree kernel as the parse tree kernel ( Collins and Duffy , 2001 )
P06-2010 kernel in a way similar to the parse tree kernel ( Collins and Duffy , 2001 )
P06-1104 Here we use the same convolution parse tree kernel as described in Collins and Duffy
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