E-commerce Review Sentiment Analysis System Based On Machine Learning

With the popularity of mobile Internet,e-commerce technology has become more and more convenient for people's lives,and has now become an inseparable part of people's lives.At the same time as the development of e-commerce,it also led to the emergence of online corpora.The potential value in a large number of corpora has begun to be concerned by researchers,which has also promoted the development of the field of natural language processing(NLP).The field of sentiment analysis,which has developed in parallel with e-commerce,has also become one of the most active fields in natural language processing(NLP).At present,a lot of research in the field of sentiment analysis mainly focuses on the processing of corpus text and the improvement of machine learning models.This article first introduces the text sentiment polarity classification technology based on machine learning in the field of sentiment analysis.After that,by studying the research results in this field at home and abroad in recent years,it analyzes the problems in the feature space and sentiment classification algorithm.Next,this paper proposes a sentiment analysis model based on comment analysis and integrated classification-ARAEC.The model uses a text analysis mechanism combining an improved sentiment expansion method and a comment corpus personality analysis method,and expands the feature vector space based on an integrated learning model that combines word embedded features to improve the classification accuracy of the integrated learning model.In order to further improve the effect of sentiment analysis,this paper proposes a sentiment classification algorithm based on SD-LS-SVM.By introducing dynamic confidence and an improved ant colony optimization algorithm,the LS-SVM algorithm's sparsity is optimized while improving the accuracy of the LS-SVM algorithm to improve the algorithm's prediction efficiency.The subject of this thesis comes from the projects commissioned by enterprises and undertakings,and the algorithm improvement methods proposed are applied to the actual project engineering.This paper combines the ARAEC model and the SD-LS-SVM algorithm to build a sentiment analysis system for e-commerce reviews based on machine learning.It can be proved that this scheme has strong practicability in practical application fields.