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Design of Intelligent English Translation Algorithms Based on a Fuzzy Semantic Network

Ping Wang1 HongGuo Cai2,*, LuKun Wang3
1 School of Foreign Languages, Jiujiang University, 332005, China
2 Department of Mathematics and Computer Science, Guangxi College of Education, Nanning, 530023, China
3 College of Intelligent Equipment, Shandong University of Science and Technology, Tai'an, 271019, China

* Corresponding Author: HongGuo Cai,

Intelligent Automation & Soft Computing 2020, 26(3), 519-529. https://doi.org/10.32604/iasc.2020.013929

Abstract

In order to improve the quality of intelligent English translation, an intelligent English translation algorithm based on the fuzzy semantic network is designed. By calculating the distance of fuzzy semantic network, classifying and ordering the English semantics to determine the optimal similarity and outputting the optimal translation results, the experiments show the average BLEU and NIST of the three test sets are 25.85 and 5.8925 respectively. The translation accuracy is higher than 95%. The algorithm can translate 246 Chinese sentences per second. This shows it is a high-performance intelligent translation algorithm and can be applied to practical intelligent translation software.

Keywords

Fuzzy semantic network; English; intelligent translation; maximum entropy; weighted hierarchy; similarity.

Cite This Article

P. Wang, H. Cai and L. Wang, "Design of intelligent english translation algorithms based on a fuzzy semantic network," Intelligent Automation & Soft Computing, vol. 26, no.3, pp. 519–529, 2020.

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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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