English Translation Stylistic Features and Syntax Translation with Application of Knowledge Mapping
Aiming at the problems of excessive instantiation complexity, poor interpretability and low generalization ability of knowledge reasoning techniques, this paper unites inductive logic programming ILP with HET neural network to construct a hybrid logic rule and neural network knowledge graph reasonin...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
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| Online Access: | https://doi.org/10.2478/amns.2023.2.01203 |
| _version_ | 1797340613871403008 |
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| author | Zhang Limin |
| author_facet | Zhang Limin |
| author_sort | Zhang Limin |
| collection | DOAJ |
| description | Aiming at the problems of excessive instantiation complexity, poor interpretability and low generalization ability of knowledge reasoning techniques, this paper unites inductive logic programming ILP with HET neural network to construct a hybrid logic rule and neural network knowledge graph reasoning model - HETIL model. The ILP is utilized to quantify the first-order logic rules, and the multi-layer rule space is constructed by arranging and combining the rules through logic symbols. The rules are instantiated and fed into the HET network, and the attention coefficients aggregate the node features to complete the end-to-end training and generate the rule learning model. Finally, the validity of the model is verified by machine translation experiments, and the results show that the accuracy of the HETIL model in syntactic structure types is more than 0.8 overall. The accuracy in terms of phrase structure reaches 0.879. The average BLEU value of the HETIL model can reach 29.24, which is 1.51 BLEU points higher than the benchmark model. Therefore, the effect of English translation by applying a knowledge graph is better than traditional machine translation. |
| first_indexed | 2024-03-08T10:05:41Z |
| format | Article |
| id | doaj.art-606c39cdb716412e8658639558ce4880 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:05:41Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-606c39cdb716412e8658639558ce48802024-01-29T08:52:40ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.2.01203English Translation Stylistic Features and Syntax Translation with Application of Knowledge MappingZhang Limin01Foreign Languages School, Xinxiang University, Xinxiang, Henan, 453003, China.Aiming at the problems of excessive instantiation complexity, poor interpretability and low generalization ability of knowledge reasoning techniques, this paper unites inductive logic programming ILP with HET neural network to construct a hybrid logic rule and neural network knowledge graph reasoning model - HETIL model. The ILP is utilized to quantify the first-order logic rules, and the multi-layer rule space is constructed by arranging and combining the rules through logic symbols. The rules are instantiated and fed into the HET network, and the attention coefficients aggregate the node features to complete the end-to-end training and generate the rule learning model. Finally, the validity of the model is verified by machine translation experiments, and the results show that the accuracy of the HETIL model in syntactic structure types is more than 0.8 overall. The accuracy in terms of phrase structure reaches 0.879. The average BLEU value of the HETIL model can reach 29.24, which is 1.51 BLEU points higher than the benchmark model. Therefore, the effect of English translation by applying a knowledge graph is better than traditional machine translation.https://doi.org/10.2478/amns.2023.2.01203knowledge graph reasoninghetil modelhybrid logic rulesilpenglish translation01a75 |
| spellingShingle | Zhang Limin English Translation Stylistic Features and Syntax Translation with Application of Knowledge Mapping Applied Mathematics and Nonlinear Sciences knowledge graph reasoning hetil model hybrid logic rules ilp english translation 01a75 |
| title | English Translation Stylistic Features and Syntax Translation with Application of Knowledge Mapping |
| title_full | English Translation Stylistic Features and Syntax Translation with Application of Knowledge Mapping |
| title_fullStr | English Translation Stylistic Features and Syntax Translation with Application of Knowledge Mapping |
| title_full_unstemmed | English Translation Stylistic Features and Syntax Translation with Application of Knowledge Mapping |
| title_short | English Translation Stylistic Features and Syntax Translation with Application of Knowledge Mapping |
| title_sort | english translation stylistic features and syntax translation with application of knowledge mapping |
| topic | knowledge graph reasoning hetil model hybrid logic rules ilp english translation 01a75 |
| url | https://doi.org/10.2478/amns.2023.2.01203 |
| work_keys_str_mv | AT zhanglimin englishtranslationstylisticfeaturesandsyntaxtranslationwithapplicationofknowledgemapping |