Chinese Natural Language Processing Based on Semantic Structure Tree

For the problem of limited rule bases and inaccurate matching of Chinese Natural Language Processing (NLP), this paper presents a new NLP method based on Semantic Structure Tree (SST). Through establishing SST, this paper calculates the evaluation index to find out the most suitable semantic combination from all possible SST. In order to improve the semantic recognition recall and precision, this paper carries out the semantic recognition and the word segmentation synchronously. Application indicates that the proposed method can guarantee high recall and precision in Chinese natural language semantic recognition.