Study on Internet Negative Information Classification Method Based on the Optimization of SVM Model

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Study on Internet Negative Information Classification Method Based on the Optimization of SVM Model

更新时间：2026-09-04

- Study on Internet Negative Information Classification Method Based on the Optimization of SVM Model
- Vol. 33, Issue 5, Pages: 115-118(2016)
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- Published：2016
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基于优化SVM模型的网络负面信息分类方法研究[J]. 微电子学与计算机, 2016, 33(5): 115-118, 123.

Study on Internet Negative Information Classification Method Based on the Optimization of SVM Model[J]. 2016, 33(5): 115-118.
基于优化SVM模型的网络负面信息分类方法研究[J]. 微电子学与计算机, 2016, 33(5): 115-118, 123. DOI：

Study on Internet Negative Information Classification Method Based on the Optimization of SVM Model[J]. 2016, 33(5): 115-118. DOI：

摘要

提出一种基于优化SVM模型的网络负面信息分类方法.该方法根据SVM建立的网络负面信息分类模型

针对模型中相关参数难以确定的问题

利用人工鱼群算法对SVM进行优化

利用优化的SVM模型对网络负面信息进行分类

实现对网络负面信息分类.实验结果表明

利用改进算法进行网络负面信息分类

能够提高网络负面信息分类的准确性和实时性

效果令人满意.

Abstract

In this paper

a network negative information classification method based on the optimization of the SVM model. The method based on SVM network negative information classification model is set up

aiming at the uncertain problems of related parameters in the model

the SVM to make use of artificial fish algorithm optimization

optimization of the SVM model is used to analyse the network negative information classification

so as to realize the network negative information classification. Experimental results show that the improved algorithm for network negative information classification can improve the accuracy and real-time network negative information classification

and effect is satisfactory.

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