LAUSR

There are many temporarily constructed dynamic words in Chinese sentences. Dynamic words are sentence building units that are not included in the general lexicon and are not suitable for further syntactic analysis. Automatic recognition and analysis of dynamic words in sentences play an important role in improving the efficiency and accuracy of Chinese automatic syntactic analysis. The existing researches on dynamic words mainly focus on the qualitative description of concepts and categories. There is no overall algorithm design and experimental exploration on automatic recognition of dynamic words. In the practice of automatic syntactic analysis, dynamic words are generally segmented, and the components are analyzed according to syntax, while the automatic recognition and analysis of dynamic words as a whole are ignored. In this study, the dynamic word is separated from syntactic analysis as the content of lexical analysis and recognized and analyzed as a whole. This paper uses the method of knowledge engineering to research and analyze dynamic words for Chinese automatic syntactic analysis based on sentence pattern structure, initially designs a knowledge representation method of dynamic words, secondly constructs the dynamic word structural mode knowledge base by annotating the dynamic words in the corpus of a certain scale of international Chinese textbooks, and finally explores the automatic recognition methods of dynamic words based on regular expressions, semantic category combinations and machine learning classification algorithms. The experimental results show that the three algorithms can cover the recognition of all types of dynamic words, and achieve relatively ideal accuracy and recall rate.