Abstract
The purpose is to adapt to the current social development and promote the English translation teaching reform. Based on the theories of deep learning (DL), text classification (TC), and the Internet of Things (IoT), this work analyzes the current situation of English translation teaching. Additionally, 100 text categories are selected from the English text corpus of Northwestern Polytechnic University as the research objects. The data are classified by the DL-based TC method and analyzed by introducing the simulated annealing algorithm. Finally, the storage and security performance of the shared IoT system are described. The results show that the proposed TC method can overcome the performance loss caused by the function extraction method, greatly reducing the training time and function space. The storage and security performance of the shared IoT system to encrypt English text will increase with the number of model iterations. Therefore, this work designs the English translation teaching-oriented shared IoT system using a DL-based TC. The finding plays an important role in subsequent English translation and enriching the theory of IoT.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
