Deep Learning Based Network News Text Classification System
Li Gao, Jie Zhao · 2022
Today, text information includes all the information in the form of natural language text, among which text information occupies an important position in life and becomes an important part of people's use of social information resources. The main purpose of this paper is to study a deep learning-based online message classification system. Based on deep learning and related text segmentation theory, this paper proposes modules such as segmentation result evaluation for the first time. Then, the first implementation and experimental results of network message segmentation are introduced and analyzed in depth. The research shows that text classification is a multidisciplinary field. Among all the literatures in the statistics, computer science has the largest number of related books in the field of text classification, with a total of 1827 books published, accounting for 87.88% of the total. In addition, it can be seen from the topic distribution map that the vocabulary has many applications and development prospects in education, news broadcasting, business management, information dissemination, mathematics and other fields.