深度学习视域下的文本特征提取方法分析

Analysis of Text Feature Extraction Method from the Perspective of Deep Learning

特征提取是当前关于文本挖掘、自然语言处理、信息检索、文本情感分析和网络舆情分析等领域的研究重难点。一方面,特征提取是基于文本挖掘系统的基本因素;另一方面,从文本分类结果的角度而言,文本特征提取性能是分类结果的重要衡量指标。因此,论文详细地阐述了传统的文本特征提取方法和深度学习视域下的文本特征提取方法,并对基于深度学习视域下的文本特征提取方法在实际应用中出现的问题进行分析和创新,以期能够帮助提高提取效率和提取质量。

Feature extraction is an important and difficult topic in the field of text mining,natural language processing,information retrieval,text sentiment analysis and network public opinion analysis.On the one hand,feature extraction is the basic factor of text mining system;on the other hand,from the perspective of text classification results,text feature extraction performance is an important measure of classification results.Therefore,this paper elaborates the traditional text feature extraction methods and text feature extraction methods from the perspective of deep learning,and analyzes and innovates the problems in the practical application of text feature extraction methods from the perspective of deep learning,so as to help improve the extraction efficiency and quality.