Comparative Experiments on Sentiment Classification for Online Product Reviews
نویسندگان
چکیده
Evaluating text fragments for positive and negative subjective expressions and their strength can be important in applications such as singleor multidocument summarization, document ranking, data mining, etc. This paper looks at a simplified version of the problem: classifying online product reviews into positive and negative classes. We discuss a series of experiments with different machine learning algorithms in order to experimentally evaluate various trade-offs, using approximately 100K product reviews from the web.
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تاریخ انتشار 2006