Automatic Knowledge Integration Method of English Translation Corpus Basedon Kmeans Algorithm

• Autores: Ping Liang, Hilal Al Bayatti
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 8, Nº. 1, 2023, págs. 381-388
• Idioma: inglés
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• Resumen

  • We propose a feature extraction method based on the Kmeans algorithm based on the text characteristics in the English translation corpus. The article first uses a sparse autoencoder unsupervised learning method to reduce dimensionality. It then uses the Kmeans clustering algorithm for text clustering. The experimental results prove that the text features extracted by the sparse autoencoder based on the Kmeans algorithm can be used for Englishtranslation corpus knowledge clustering to achieve automatic integration. And this method can effectively solve the problems of high-dimensional, sparse, and noisy texts in the English translation corpus. The algorithmmentioned in the article can significantly improve the accuracy of the clustering results.