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

作者：Gong, Yunlu^*; Lu, Nannan; Zhang, Jiajian

来源：Concurrency and Computation: Practice and Experience (CCPE) , 2019, 31(10): e4779.

DOI：10.1002/cpe.4779

• dynamic characteristics
• emotional information
• emotional semantic analysis
• massive information

With the development of network technology, people are facing more and more massive information. How to extract emotional information in massive information rapidly has received more and more attention from people. This paper introduces the principle and structure of the traditional emotional model. Different personality, emotional states, and external stimuli will have different effects on emotional semantic analysis. In addition, this paper has proposed emotional semantic analysis method based on wake-sleep and SVM method. The model starts from the description and calculation of the dynamic characteristics of emotions and more fully predicts the process characteristics that describe the evolution of emotions. Search and category browsing allows users to quickly access these information points. In addition, this paper provides a deep learning fusion algorithm in emotional semantic analysis, introduces its reference implementation and related key technologies, and supports business intelligence to a certain extent, and it has a strong application prospect on the network data information.

• 出版日期2019-5-25
• 单位中国矿业大学（北京）; 上海大学