To model the importance of a word, we include the tf-idf (term frequency -inverse document frequency) values of the dependent and head words to the formula and form the TF-IDF Based Approximate Bigram Kernel (TABK) as defined below: where N (A) is the normalizer function: and sim t is defined as: TABK does not encourage consecutive bigram matches that form a subtree in the dependency trees.
a common subtree in the dependency trees of two sentences means that these sentences contain similar substructures.