Zeyi Xu
China University of Geosciences (Wuhan), Wuhan, Hubei, China.
*Corresponding author: Zeyi Xu
Abstract
Natural language processing (NLP) technology plays an important role in the field of artificial intelligence, and shows its advanced nature and outstanding advantages. With the rise of deep learning, it is widely used in the processing of language, image and text data. The introduction of deep learning has led to great changes in NLP, greatly changing the previous processing methods, and improving the computational efficiency of processing tasks such as named entity recognition, intention recognition, parsing and speech recognition. The application of deep learning in NLP is of great significance to research and practice. By applying deep learning techniques to NLP, we are able to better understand and process natural language. Deep learning models can learn and capture complex semantic and contextual relationships from large-scale data, so as to achieve more accurate and efficient natural language processing. This method has achieved remarkable results in tasks such as text classification, sentiment analysis, machine translation and dialogue systems.
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How to cite this paper
Research on Deep Learning in Natural Language Processing
How to cite this paper: Zeyi Xu. (2023) Research on Deep Learning in Natural Language Processing. Advances in Computer and Communication, 4(3), 196-200.
DOI: http://dx.doi.org/10.26855/acc.2023.06.018