Dependency language Parsing model based on word clustering

By incorporating linguistic features such as semantic dependency and syntactic relations,a novel statistical Parsing model was proposed.The model was constructed on cluster,and the problem of data sparseness was not serious.The model took advantage of a few semantic dependencies at the same time,and it was a parser based on lexicalized model.Experiments were conducted for the refined statistical parser.The results show that precision and recall are 88.14% and 86.93%,respectively,and comprehensive factor is improved by 6.09% compared with that of the head-driven parsing model.