Application of Bayesian Network Reasoning Algorithm in Emotion Classification
20th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2021
; : 1214-1219, 2021.
Article
in English
| Scopus | ID: covidwho-1788794
ABSTRACT
In the early stage of covid-19 disease transmission, it is easy to lead to public panic and dissatisfaction without timely information feedback. In order to solve this problem, this paper constructs an emotion classification and prediction algorithm based on Bayesian network reasoning by analyzing the variable elimination algorithm, connection tree reasoning algorithm and Gibbs sampling algorithm in Bayesian network reasoning algorithm. The algorithm can quickly identify the emotions of Internet users from the communication with low computational resources, and provide reference for the relevant departments to formulate the correct public opinion guidance strategy. © 2021 IEEE.
Bayesian network; Emotion classification; NP hard; uncertainty reasoning; variable elimination order; Social aspects; Trees (mathematics); Application of Bayesian networks; Bayesia n networks; Disease transmission; Information feedback; NP-hard; Reasoning algorithms; Variable elimination; Bayesian networks
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Databases of international organizations
Database:
Scopus
Language:
English
Journal:
20th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2021
Year:
2021
Document Type:
Article
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