Design of chinese natural language in fuzzy boundary determination algorithm based on big data

In this study, we proposed a new method to determine the fuzzy boundary of natural language based on big data. According to the principle of natural language recognition, the acoustic characteristics of the analysis, natural language acoustic model and statistical model is established, Viterbi decoding algorithm has been applied for natural language decoding, and take this as the basis, we implemented deep learning methods for natural language feature extraction, and used the support vector machine method for classification, according to the characteristics of natural language significant division, in accordance with the constraints, combined with large data analysis method, to determine the natural language fuzzy boundary. Experimental results indicate that using the proposed method, compared with existing methods the recall and accuracy rate have been improved.