<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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 English translation 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 algorithm mentioned in the article can significantly improve the accuracy of the clustering results.</p>
</abstract>

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 English translation 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 algorithm mentioned in the article can significantly improve the accuracy of the clustering results.

Automatic Knowledge Integration Method of English Translation Corpus Based on Kmeans Algorithm

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

We propose a feature extraction method based on the Kmeans algorithm based on the text characteristics in the English translation corpus. The article first...

Automatic Knowledge Integration Method of English Translation Corpus Based on Kmeans Algorithm

Online veröffentlicht: 11. Juni 2023

Seitenbereich: 381 - 388

Eingereicht: 19. Jan. 2022

Akzeptiert: 28. März 2022

DOI: https://doi.org/10.2478/amns.2022.2.00019

Schlüsselwörter
Kmeans algorithm, Deep learning, English translation, Feature extraction, Corpus, Automated integration

© 2023 Ping Liang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

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Automatic Knowledge Integration Method of English Translation Corpus Based on Kmeans Algorithm

Online veröffentlicht: 11. Juni 2023

Seitenbereich: 381 - 388

Eingereicht: 19. Jan. 2022

Akzeptiert: 28. März 2022

DOI: https://doi.org/10.2478/amns.2022.2.00019

SchlüsselwörterKmeans algorithm, Deep learning, English translation, Feature extraction, Corpus, Automated integration

© 2023 Ping Liang et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Schlüsselwörter
Kmeans algorithm, Deep learning, English translation, Feature extraction, Corpus, Automated integration