Recent Applications of Machine Learning in Natural Language Processing (NLP)
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The digital age has seen a significant transformation with the integration of machine learning into natural language processing (NLP). This shift highlights the growing importance of data-driven decisions and human-like interfaces. This Special Issue explores the latest applications of machine learning in NLP, showcasing its potential to revolutionize human-computer interactions. NLP covers a wide range of tasks, including sentiment analysis (which detects emotions in text) and voice processing (which enhances auditory interactions). Entity recognition and syntax analysis are crucial for infor...
The digital age has seen a significant transformation with the integration of machine learning into natural language processing (NLP). This shift highlights the growing importance of data-driven decisions and human-like interfaces. This Special Issue explores the latest applications of machine learning in NLP, showcasing its potential to revolutionize human-computer interactions. NLP covers a wide range of tasks, including sentiment analysis (which detects emotions in text) and voice processing (which enhances auditory interactions). Entity recognition and syntax analysis are crucial for information retrieval and understanding language structure. Advances in machine translation and summarization have made multilingual communication smoother. Large language models are improving question-answering systems and chatbots, making interactions more natural. The combination of image segmentation and NLP is also enhancing multimedia understanding.
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