Design of Intelligent Recognition English Translation Model based on Improved Apriori Algorithm

Abstract

Natural language processing is a method in computer science to obtain and analyze meaning from human language and interact with human in an intelligent way. The translation recognition results of Apriori algorithm model have data points overlapping, and the accuracy can not be effectively guaranteed. In order to identify phrases accurately, an intelligent recognition model of machine translation based on improved Apriori algorithm is proposed for the low accuracy of conventional algorithm model. This algorithm creates a corpus for marking phrases, so that phrases can be searched automatically. In addition, a machine translation intelligent recognition model is created to plan the intelligent recognition model based on data collection, processing and output. The information is collected and processed in a planned way, and the feature parameters are extracted to realize the intelligent recognition of machine translation. The designed machine translation intelligent recognition model is experimentally analyzed and the experimental data are recorded. The experimental analysis shows that the designed machine translation recognition model can finish translation work. The algorithm overcomes the disadvantages of Apriori, improves the operation speed and processing performance, is more suitable for machine translation tasks, and provides a novel idea of intelligent machine translation.