Modeling and Analysis of Translation Ability of Applied English Talents Based on Data Mining Algorithm

Abstract

In order to improve the security of modeling data of translation ability of applied English talents, a translation ability model of applied English talents based on principal component analysis and big data mining is proposed. A data storage structure feature analysis and integrated processing model for modeling data of applied English talents' translation ability is constructed. A semantic text feature coding control model for modeling data of applied English talents' translation ability is constructed by using distributed integration of semantic ontology and model base and joint control of English talents' translation. This paper constructs the password structure of principal component feature distribution of applied English talents' translation ability modeling data, realizes semantic roughness construction of applied English talents' translation ability modeling data and talents' application ability modeling according to the coding feature distribution of applied English talents' translation ability modeling protocol, and adopts improved BP neural network to realize the construction of applied English talents' translation ability model. The test shows that this method has better data security assessment ability and higher confidence level in modeling the translation ability of applied English talents, and improves the translation ability planning ability of applied English talents.