Global translation optimization of semantic segmentation of English long sentences based on HNC theory
The complex structure of long English sentences interferes with the semantic correlation analysis in the process of machine translation,affecting the quality of machine translation.Therefore,an optimiza-tion method of semantic segmentation of long English sentences based on Hierarchical Network of Concepts(HNC)theory is designed.Feature semantic blocks of long English sentences are preprocessed to construct sentence logic and sequence.Sentence semantic segmentation algorithm based on HNC theory is used to segment long English sentences and obtain information entropy data of short sentences.Short sentences are translated with nonlinear spectral features that can automatically adapt to matching semantics,identify the features of semantic information of the text to be translated,adjust the order of translated short sentences,and then synthesize them to obtain global translation results.The experiment results show that the proposed method has a high segmentation accuracy,can accurately identify long English sentences,and has a high quality of machine translation.
semantic segmentationlong English sentencesMTHNC theorysentence segmentation al-gorithm
NETL
NSTL
万方数据
