Deep Structured Learning for Natural Language Processing

Abstract

The real-time and dissemination characteristics of network information make net-mediated public opinion become more and more important food safety early warning resources, but the data of petabyte (PB) scale growth also bring great difficulties to the research and judgment of network public opinion, especially how to extract the event role of network public opinion from these data and analyze the sentiment tendency of public opinion comment. First, this article takes the public opinion of food safety network as the research point, and a BLSTM-CRF model for automatically marking the role of event is proposed by combining BLSTM and conditional random field organically. Second, the Attention mechanism based on vocabulary in the field of food safety is introduced, the distance-related sequence semantic features are extracted by BLSTM, and the emotional classification of sequence semantic features is realized by using CNN. A kind of Att-BLSTM-CNN model for the analysis of public opinion and emotional tendency in the field of food safety is proposed. Finally, based on the time series, this article combines the role extraction of food safety events and the analysis of emotional tendency and constructs a net-mediated public opinion early warning model in the field of food safety according to the heat of the event and the emotional intensity of the public to food safety public opinion events.

Application of an Improved Convolutional Neural Network Algorithm in Text Classification

“…To evaluate the performance of the proposed algorithm, the CNN model [27], the TF-IDF model [28], and the proposed CNN-SVM model in this experiment are compared for handling the same data set. The experimental operation platform is the Windows 10 Professional operating system, with 16 GB memory and 2.8 GHz CPU.…”

Research on online public opinion dissemination and emergency countermeasures of food safety in universities—take the rat head and duck neck incident in China as an example

“…Therefore, colleges and universities should conduct food safety inspections, regularly inspect the operation of canteens, increase penalties for canteens, and provide students with more channels to safeguard their rights ( 53 ). Once a food safety incident is discovered, identify risks as early as possible and adopt multiple contingency plans to intervene as soon as possible ( 54 ). The second is timely intervention and correct response.…”