Data sparseness severely affects the system performances of syntactic parsing, and syntactic structures are unities of syntactic forms and semantic contents. Based on the labeling of semantic information, a word clustering model and algorithm is proposed. And a head-driven statistical syntactic parsing model based on semantic category is established. The problem of data sparseness is successfully solved, and the system performances of syntactic parsing are obviously enhanced. Experiments are conducted for the head-driven statistical syntactic parsing model based on semantic category. It achieves 88.73% precision and 88.26% recall. F measure is improved 8.39% compared with the distinctive head-driven parsing model.