Go Climb a Dependency Tree and Correct the Grammatical Errors

State-of-art systems for grammar error correction often correct errors based on word sequences or phrases. In this paper, we describe a grammar error correction system which corrects grammatical errors at tree level directly. We cluster all error into two groups and divide our system into two modules correspondingly: the general module and the special module. In the general module, we propose a TreeNode Language Model to correct errors related to verbs and nouns. The TreeNode Language Model is easy to train and the decoding is efficient. In the special module, two extra classification models are trained to correct errors related to determiners and prepositions. Experiments show that our system outperforms the state-of-art systems and improves the F1 score.