Modeling of the English Translation Complex System Based on Discrete Data Mining

Abstract

This paper provides an in-depth analysis and research on the application of web discrete data mining in modeling complex systems for English translation. This paper adopts association rule mining, clustering, and classification methods to deeply analyze English translation, mine the interesting rules in it, find out the interinfluence relationship of system modeling and the relationship between translation behaviors, analyze and compare different data mining methods, and make an evaluation of the mining results to provide a scientific reference basis for the relevant decision-making scheme of the English translation. The paper elaborates the relevant concepts of data mining and the theoretical basis and analysis process of association rule mining, clustering rule mining, and classification rule mining methods. The application of data mining techniques in modeling and analysis of complex systems of the English translation is highlighted, and these three mining methods are used to analyze a set of English sample data: through the analysis of the correlation of different English translations, some feasible suggestions are provided for the order of translation settings; through the analysis of clustering of English translations, the shortcomings of traditional translation methods are made up; through the analysis of the factors affecting the accuracy of English translations factors, a useful reference is provided on how to improve English translation and then improve the quality of translation.