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- W2931362078 abstract "Based on the theory of emotional semantic analysis and modal particles analysis, marked the emotional sentiment, established the database of modal particles emotion, and combined with the analysis of traditional text emotion, this paper analyzes the emotional sentiment and intensity of network chat text. Through the machine learning and natural language computing technology in big data technology, using multi-mode learning method, the chat text statement is trained and learnt, the emotion is automatically calculated and predicted, and the accuracy of text sentiment analysis is increased. This paper aim to find emotional security risks in time. Thus the emotional security risks of Internet chat to take effective security warning." @default.
- W2931362078 created "2019-04-11" @default.
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- W2931362078 date "2019-01-01" @default.
- W2931362078 modified "2023-09-27" @default.
- W2931362078 title "The Indication of Network Chat Text Security Based on the Analysis of Modal Particles Emotion" @default.
- W2931362078 cites W2351739686 @default.
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- W2931362078 doi "https://doi.org/10.1007/978-3-030-15740-1_118" @default.
- W2931362078 hasPublicationYear "2019" @default.
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