LSTM sentiment analysis based on documentary review texts
In this paper,the CBOW algorithm is first used to make efficient and low-dimensional vector representations of comments crawled by Python,and then these vectors are trained using the LSTM model.This paper also compares the performance of the LSTM model with Naive Bayes,decision trees,random forests,and RNN in terms of predictive ability through experiments.The paper is rigorously structured.A comprehensive model comparison is provided.Experimental results show that the LSTM model has higher accuracy and has certain applicability.
long short-term memoryWord2veccomment on textsentiment analysis
NETL
NSTL
万方数据
