基于优化SVM模型的网络负面信息分类方法研究

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

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.