KNN algorithm based article translation method

Abstract

Provided is a KNN algorithm based article translation method. The method comprises the steps of: firstly, splitting a relatively large article, extracting a keyword from an article to be translated and classifying the article; and obtaining an optimal allocation result by using an algorithm to match a K value. The invention is mainly about preprocessing articles that are used for training and mail data to be classified; performing textual representation on the preprocessed articles that are used for training and mail data to be classified; using a genetic algorithm to perform feature extraction on the textually represented articles that are used for training and on mail data to be classified; performing classification training on the extracted features of the articles that are used for training; using the optimized sample set KNN algorithm to perform classification training, so as to construct a text classifier; and applying the text classifier to the articles to be classified after the feature extraction, so as to obtain a classification result of the articles to be classified. The method provided by the invention can be better applied to an article text information mining system.

Description

technical field [0001] A manuscript translation optimization method based on the KNN algorithm, which uses the K-nearest neighbor node algorithm to classify manuscripts by cutting and optimizing the training set, belongs to the fields of text mining, natural language processing, and computer technology. Background technique [0002] The information age and networking have brought about great changes in the way translation works. Use the translation process management platform to store talent data according to different objects. When there is a translation task, according to the language of the translation project, the type of article, the professional field, and the customer's requirements for translation quality and time limit, we can call the most suitable translators and reviewers to form a project team for translation, thereby improving translation efficiency and saving translation costs, ensure translation quality, and optimize project management. [0003] The current...

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a manuscript translation optimization method based on the KNN algorithm to solve the problem of low efficiency and accuracy of the traditional manual classification method, and introduces the mutual information value into the genetic algorithm in the feature extraction step. The advantages of the two extraction methods can be combined to make the feature extraction results more reliable, so that the entire text classification can be better applied to the manuscript text information mining system

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