Selecting Attributes for Opinion Mining in Different Domains

International Journal of Artificial Intelligence and Knowledge Discovery

Vani Raja¹ 

[1] Research scholarSathyabama Universitydept of CSE

关键词: Accuracy;    Bagging;    Genetic Algorithm (GA);    Naive Bayes (NB);    Sentiment Mining;    Support Vector Machine;   

DOI  :  

学科分类：建筑学

来源: RG Education Society

【 摘 要 】

Sentiment Classification is an important tool to handle and summarize the general opinions about multi domain reviews, movie reviews and music reviews.  Various machine learning algorithms have been studied in previous literatures. In this paper, we evaluate the accuracy of movie reviews and multi domain reviews and We used Information Gain, Chi Squared and Weight by Support Vector feature selection methods and TF-IDF weighting scheme along with classification algorithms such as KNN, SVM, SVM-PSO and NB. We compared the accuracy of SVM with and without feature selection. An empirical result shows that SVM approach with SVMW feature selection method outperformed other classification algorithms.

【 授权许可】

Unknown