Research on Text Classification Methods Based on Neural Network
摘要
Large-scale text analysis is an important means of understanding and finding value of big data.Hence text classification,as a classical natural language processing problem,has been widely concerned by researchers,and its main research direction is artificial neural network due to its excellent performance in text analysis.This paper introduces the history of Convolutional Neural Network(CNN),Recurrent Neural Network(RNN),recursive neural network structure and the pretraining model applied to text classification.Then this paper compares classification performance of different models based on the common dataset,demonstrating that artificial neural network structure can reduce manual characterization work by automatically obtaining text features,and thus improve text classification effects.On this basis,this paper prospects the future research directions of text classification.