论文信息 - Sentiment text classification of customers reviews on the Web based on SVM

Sentiment text classification of customers reviews on the Web based on SVM

As a developing endeavor of data mining on semi-structured information, sentiment analysis to the comments on the Internet has aroused people's great interest recently. This paper analysis the influence of different stop word removal methods on the result of text classification and represent the more effective stop word removal list. The experiment bases on the sentiment comments which have been grasped on the Web, using two different kinds of feature selection, choose the TF-IDF function to calculate the feature weights. Implement the classification with the technology of SVM.

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