Building semantically annotated corpus for text classification of Indian defence news articles

Psychological Education Health Assessment Problems Based on Improved Constructive Neural Network

“…In this regard, Zhou used the Bi-LSTM structure to replace the convolution and pooling process of Text CNN to express the contextual information of text and extracted the valuable information in text by two-dimensional convolution and pooling in two dimensions, and this method effectively improved the accuracy of text classification for various application scenarios such as news classification, question classification, and sentiment classification ( Zhou et al, 2016 ; Shaikh et al, 2021 ). Liu used a mathematical model based on deep learning algorithms for the personality prediction of social network users ( Joulin et al, 2016 ; Cui and Zang, 2021 ; Kanekar et al, 2021 ; Ren et al, 2021 ). Yates analyzed the process of detecting mental health problems of online forum users and concluded that feature construction is the most tedious task in the detection process, for which convolutional neural networks were invoked for feature construction, which greatly simplified the workflow ( Yates et al, 1709 ; He et al, 2021 ).…”

Prediction of News Popularity Based on Deep Neural Network

“…In addition, online hot news prediction has important application value; firstly, it can enable the government to grasp the trend of public opinion in a timely manner, which is convenient for the government to manage public opinion and grasp and handle sudden public events; secondly, it can help news websites manage the release locations of different news, Put hot news in the area that users pay more attention to, thereby increasing the influence of news websites; at the same time, it promotes the public to pay attention to the current hot news in a timely manner, and triggers thinking about daily life from the news, thereby improving the quality of life. For example, when hot news related to telecommunication fraud occupies the homepage of major fine-textured websites, it can increase people's attention to and beware of telecommunication fraud, and help people learn the relevant knowledge of preventing telecommunication fraud [9][10][11][12]. Network news has become the main source of network waves and public opinion, and it is of great theoretical and applied value to accurately predict hot news and attract public attention and discussion [13][14][15].…”