Research on Web text classification algorithm based on improved CNN and SVM

摘要

Web text classification is one of the research focuses and core technologies in Web information retrieval and data mining, and it has been widely concerned and developed rapidly in recent years. The convolutional neural network (CNN), as a kind of deep learning model, can extract the features of the text data accurately and reduce the complexity of models at the same time. The support vector machine (SVM) has always had the advantages of being effective and stable in traditional machine learning algorithms. According to the characteristics of CNN and SVM, this paper proposes a new method of Web text classification based on the improved CNN and SVM, using the CNN model with the five-layer network structure to extract text feature and then classify and predict by using SVM. Finally, it will obtain an excellent effect on mixed text data set.