Classification of sentiment reviews using n-gram machine learning approach
作者：
Highlights：
• A large number of sentiment reviews, blogs and comments present online.
• These reviews must be classified to obtain a meaningful information.
• Four different supervised machine learning algorithm used for classification.
• Unigram, Bigram, Trigram models and their combinations used for classification.
• The classification is done on IMDb movie review dataset.
摘要
•A large number of sentiment reviews, blogs and comments present online.•These reviews must be classified to obtain a meaningful information.•Four different supervised machine learning algorithm used for classification.•Unigram, Bigram, Trigram models and their combinations used for classification.•The classification is done on IMDb movie review dataset.
论文关键词：Sentiment analysis,Naive Bayes (NB),Maximum Entropy (ME),Stochastic Gradient Descent (SGD),Support Vector Machine (SVM),N-gram,IMDb dataset
论文评审过程：Received 3 March 2015, Revised 15 March 2016, Accepted 16 March 2016, Available online 24 March 2016, Version of Record 6 April 2016.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.03.028
