Author
Abstract
In the era of big data, data are ubiquitous. The proliferation of data leads to a surge in the demand for communication, which in turn promotes a surge in the demand for language services. Big data technology is a comprehensive technology, and its important feature is a more active technological factor, where technological development and technological innovation dominate, which will have an incalculable impact on the development of the translation industry. In the language service industry, much information that used to be difficult to quantify will be transformed into data for storage and processing, and a large number of complex items to be translated will gradually surface. Therefore, it is the general trend of the translation industry to stimulate and utilize the unexplored values hidden inside the data and develop the blue ocean of the language service industry. Traditional translation researchers are confined to the study of language and text and are not fully aware of it. The huge role played by translation technology in today’s business environment, and the traditional translation theory can hardly describe and explain the new modern translation technology phenomenon and translation technology activities. Whether we are ready for it or not, the rapid development of translation technology in the era of big data will lead to significant changes in translation inquiry and translation teaching on a global scale. The integration and development of translation with cloud computing, big data, the Internet, and artificial intelligence are driving a series of innovations in the traditional translation model. The development of translation technologies and tools is breaking new ground, rapidly expanding into all aspects of the translation industry and triggering disruptive changes in the language service industry.
Suggested Citation
Xiaoyu Li & Baiyuan Ding, 2022.
"The Impact of Big Data Technology on Phrase and Syntactic Coherence in English Translation,"
Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, June.
Handle:
RePEc:hin:jnlmpe:1428748
DOI: 10.1155/2022/1428748
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