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      Retracted: A Chaotic Neural Network Model for English Machine Translation Based on Big Data Analysis

      retraction
      Computational Intelligence and Neuroscience
      Hindawi

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          Abstract

          This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation The presence of these indicators undermines our confidence in the integrity of the article's content and we cannot, therefore, vouch for its reliability. Please note that this notice is intended solely to alert readers that the content of this article is unreliable. We have not investigated whether authors were aware of or involved in the systematic manipulation of the publication process. Wiley and Hindawi regrets that the usual quality checks did not identify these issues before publication and have since put additional measures in place to safeguard research integrity. We wish to credit our own Research Integrity and Research Publishing teams and anonymous and named external researchers and research integrity experts for contributing to this investigation. The corresponding author, as the representative of all authors, has been given the opportunity to register their agreement or disagreement to this retraction. We have kept a record of any response received.

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          • Record: found
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          A Chaotic Neural Network Model for English Machine Translation Based on Big Data Analysis

          In this paper, the chaotic neural network model of big data analysis is used to conduct in-depth analysis and research on the English translation. Firstly, under the guidance of the translation strategy of text type theory, the translation generated by the machine translation system is edited after translation, and then professionals specializing in computer and translation are invited to confirm the translation. After that, the errors in the translations generated by the machine translation system are classified based on the Double Quantum Filter-Muttahida Quami Movement (DQF-MQM) error type classification framework. Due to the characteristics of the source text as an informative academic text, long and difficult sentences, passive voice, and terminology translation are the main causes of machine translation errors. In view of the rigorous logic of the source text and the fixed language steps, this research proposes corresponding post-translation editing strategies for each type of error. It is suggested that translators should maintain the logic of the source text by converting implicit connections into explicit connections, maintain the academic accuracy of the source text by adding subjects and adjusting the word order to deal with the passive voice, and deal with semitechnical terms by appropriately selecting word meanings in postediting. The errors of machine translation in computer science and technology text abstracts are systematically categorized, and the corresponding post-translation editing strategies are proposed to provide reference suggestions for translators in this field, to improve the quality of machine translation in this field.
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            Author and article information

            Contributors
            Journal
            Comput Intell Neurosci
            Comput Intell Neurosci
            cin
            Computational Intelligence and Neuroscience
            Hindawi
            1687-5265
            1687-5273
            2023
            2 August 2023
            2 August 2023
            : 2023
            : 9782532
            Affiliations
            Article
            10.1155/2023/9782532
            10412337
            186268f6-a800-4674-8a51-69ad11912e22
            Copyright © 2023 Computational Intelligence and Neuroscience.

            This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            History
            : 1 August 2023
            : 1 August 2023
            Categories
            Retraction

            Neurosciences
            Neurosciences

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