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 Lan-guage Model is easy to train and the de-coding 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 sys-tems and improves the F1 score.