A New Training Idea of Machine Learning in NLP. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Zhou, Di
• Is Part Of: Journal of physics. Volume 1861:Issue 1(2021)
• Publication Date: 2021-03
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1861/1/012083
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Natural language processing is an important direction in the field of computer science and artificial intelligence. It studies various theories and methods that enable effective communication between humans and computers in natural language. Generally speaking, NLP can be divided into the following areas, including text retrieval, sentiment analysis, semantic role labeling, machine translation and dialogue systems. Nowadays, although artificial intelligence has achieved a certain degree of achievements in the dialogue system, there is still room for improvement. This article proposes a way to deal with multiple interactive dialogues between man and machine, so that machine dialogue can take more about the content of the conversation before and after into account and the performance of machine is closer to the real human dialogue.