Application of deep learning fusion algorithm in natural language processing in emotional semantic analysis

摘要

With the development of network technology, people are facing more andmore massive information.How to extract emotional information inmassive information rapidly has received more andmore attention from people. This paper introduces the principle and structure of the traditionalemotional model. Different personality, emotional states, and external stimuli will have differenteffects on emotional semantic analysis. In addition, this paper has proposed emotional semanticanalysis method based on wake-sleep and SVM method. The model starts from the descriptionand calculation of the dynamic characteristics of emotions and more fully predicts the processcharacteristics that describe the evolution of emotions. Search and category browsing allowsusers to quickly access these information points. In addition, this paper provides a deep learningfusion algorithm in emotional semantic analysis, introduces its reference implementation andrelated key technologies, and supports business intelligence to a certain extent, and it has a strongapplication prospect on the network data information.