English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation Model
Translation as a bridge between different cultures has received significant attention in recent years, especially with the rise of globalization and the increasing communication between nations. Translation has become a crucial tool for connecting people, promoting cross-cultural understanding, and...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-12-01
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| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2023.2201145 |
| _version_ | 1797684804525752320 |
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| author | Rui Ma Di Shao |
| author_facet | Rui Ma Di Shao |
| author_sort | Rui Ma |
| collection | DOAJ |
| description | Translation as a bridge between different cultures has received significant attention in recent years, especially with the rise of globalization and the increasing communication between nations. Translation has become a crucial tool for connecting people, promoting cross-cultural understanding, and facilitating international trade, academic exchange, and outbound tourism. With the advancement of information technology, research on improving English translation algorithms has become a hot topic. This is due to the complexities and variability of language, where words can have different meanings in different contexts. To address the issue of semantic coherence in current English translation proofreading systems, this paper proposes a semantic ontology translation model that utilizes fuzzy mapping to translate English and selects the most semantically appropriate translation using a decision function. The contributions of this research are twofold. Firstly, it provides a new approach to English translation proofreading by incorporating semantic ontology and fuzzy mapping. Secondly, it demonstrates the effectiveness of this approach through the improved efficiency and accuracy of English proofreading. The key findings of this study show that the proposed semantic ontology translation model can significantly improve the semantic coherence of English translation proofreading. This makes this article different from other studies by offering a unique solution to the problem of semantic coherence in English translation proofreading. |
| first_indexed | 2024-03-12T00:35:05Z |
| format | Article |
| id | doaj.art-61679e466a7444c2a0a3f5828d87f3b4 |
| institution | Directory Open Access Journal |
| issn | 0883-9514 1087-6545 |
| language | English |
| last_indexed | 2024-03-12T00:35:05Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Artificial Intelligence |
| spelling | doaj.art-61679e466a7444c2a0a3f5828d87f3b42023-09-15T10:01:06ZengTaylor & Francis GroupApplied Artificial Intelligence0883-95141087-65452023-12-0137110.1080/08839514.2023.22011452201145English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation ModelRui Ma0Di Shao1North China Institute of Aerospace EngineeringNorth China Institute of Aerospace EngineeringTranslation as a bridge between different cultures has received significant attention in recent years, especially with the rise of globalization and the increasing communication between nations. Translation has become a crucial tool for connecting people, promoting cross-cultural understanding, and facilitating international trade, academic exchange, and outbound tourism. With the advancement of information technology, research on improving English translation algorithms has become a hot topic. This is due to the complexities and variability of language, where words can have different meanings in different contexts. To address the issue of semantic coherence in current English translation proofreading systems, this paper proposes a semantic ontology translation model that utilizes fuzzy mapping to translate English and selects the most semantically appropriate translation using a decision function. The contributions of this research are twofold. Firstly, it provides a new approach to English translation proofreading by incorporating semantic ontology and fuzzy mapping. Secondly, it demonstrates the effectiveness of this approach through the improved efficiency and accuracy of English proofreading. The key findings of this study show that the proposed semantic ontology translation model can significantly improve the semantic coherence of English translation proofreading. This makes this article different from other studies by offering a unique solution to the problem of semantic coherence in English translation proofreading.http://dx.doi.org/10.1080/08839514.2023.2201145 |
| spellingShingle | Rui Ma Di Shao English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation Model Applied Artificial Intelligence |
| title | English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation Model |
| title_full | English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation Model |
| title_fullStr | English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation Model |
| title_full_unstemmed | English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation Model |
| title_short | English Translation proofreading System based on Information Technology: Construction of semantic Ontology Translation Model |
| title_sort | english translation proofreading system based on information technology construction of semantic ontology translation model |
| url | http://dx.doi.org/10.1080/08839514.2023.2201145 |
| work_keys_str_mv | AT ruima englishtranslationproofreadingsystembasedoninformationtechnologyconstructionofsemanticontologytranslationmodel AT dishao englishtranslationproofreadingsystembasedoninformationtechnologyconstructionofsemanticontologytranslationmodel |