A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm

In order to improve the accuracy and efficiency of the classification of network ideological and political resources and promote the efficiency of ideological education, a research on the classification of network ideological and political resources based on the improved SVM algorithm is proposed. W...

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Autor principal:	WenXia Wang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology (General) T1-995 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/6a79b591750c4a939babd05ee875b133
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spelling	oai:doaj.org-article:6a79b591750c4a939babd05ee875b1332021-11-22T01:10:23ZA Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm1939-012210.1155/2021/2133042https://doaj.org/article/6a79b591750c4a939babd05ee875b1332021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2133042https://doaj.org/toc/1939-0122In order to improve the accuracy and efficiency of the classification of network ideological and political resources and promote the efficiency of ideological education, a research on the classification of network ideological and political resources based on the improved SVM algorithm is proposed. We analyze the characteristics and current situation of network ideological and political resources and conclude that the method elements are open and technical. The ontology elements are rich and shared, and the behavioral elements are autonomous and interactive. Three types of network ideological and political resources are proposed: the main resource, content resource, and means resource. The particle swarm algorithm is used to improve the SVM algorithm. In the process of constructing the SVM classifier, the fuzzy membership function is introduced, the classification problem of network ideological and political resources is converted into a secondary planning problem, and the accuracy of network ideological and political resources is finally realized. Simulation results show that the use of improved algorithms to classify network ideological and political resources can improve the accuracy and efficiency of network abnormal data classification.WenXia WangHindawi-WileyarticleTechnology (General)T1-995Science (General)Q1-390ENSecurity and Communication Networks, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995 Science (General) Q1-390
spellingShingle	Technology (General) T1-995 Science (General) Q1-390 WenXia Wang A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm
description	In order to improve the accuracy and efficiency of the classification of network ideological and political resources and promote the efficiency of ideological education, a research on the classification of network ideological and political resources based on the improved SVM algorithm is proposed. We analyze the characteristics and current situation of network ideological and political resources and conclude that the method elements are open and technical. The ontology elements are rich and shared, and the behavioral elements are autonomous and interactive. Three types of network ideological and political resources are proposed: the main resource, content resource, and means resource. The particle swarm algorithm is used to improve the SVM algorithm. In the process of constructing the SVM classifier, the fuzzy membership function is introduced, the classification problem of network ideological and political resources is converted into a secondary planning problem, and the accuracy of network ideological and political resources is finally realized. Simulation results show that the use of improved algorithms to classify network ideological and political resources can improve the accuracy and efficiency of network abnormal data classification.
format	article
author	WenXia Wang
author_facet	WenXia Wang
author_sort	WenXia Wang
title	A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm
title_short	A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm
title_full	A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm
title_fullStr	A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm
title_full_unstemmed	A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm
title_sort	classification method of network ideological and political resources using improved svm algorithm
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/6a79b591750c4a939babd05ee875b133
work_keys_str_mv	AT wenxiawang aclassificationmethodofnetworkideologicalandpoliticalresourcesusingimprovedsvmalgorithm AT wenxiawang classificationmethodofnetworkideologicalandpoliticalresourcesusingimprovedsvmalgorithm
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A Classification Method of Network Ideological and Political Resources Using Improved SVM Algorithm

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