Research on Japanese-Chinese Statistical Machine Translation Based on Improved Ant Colony Algorithm

In order to effectively overcome ambiguity, the bottleneck problem of Chinese machine translation, and improve the accuracy of Chinese automatic word segmentation, the improved ant colony algorithm and grey entropy are used to study the problem of Chinese automatic word segmentation. Based on the word segmentation model, the accuracy of word segmentation is measured by grey entropy. Ant colony algorithm has the advantages of excellent distributed computing, information positive feedback mechanism and heuristic search, and has shown great development potential in solving complex optimization problems. Multi-strategy machine translation is a development direction of machine translation system today. This paper discusses the core technologies and algorithms used by each translation core subsystem in a Multi Strategy Chinese Japanese machine translation system, including Chinese analysis subsystem using lexical analysis, syntactic analysis and semantic role tagging, machine translation subsystem based on translation memory technology using double index technology A case-based machine translation subsystem with syntactic tree fragments as templates and a machine translation subsystem integrating valence patterns and fragment analysis. Among many application algorithms, ant colony algorithm has attracted extensive attention since it was proposed. An application example shows the effectiveness of the method. This method is of great significance to improve the level of machine translation and digitization in China.