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- W1993403239 abstract "Sentiment classification has attracted increasing interest from Natural Language Processing. The goal of sentiment classification is to automatically identify whether a given piece of text expresses positive or negative opinion towards a topic of interest. We present the standpoint that uses a human model based on random process to determine text polarity classification. Experiment results showed that on movie review corpus, the human modeling approach has a relatively higher accuracy than that of SVMs and Naive Bayes classifier." @default.
- W1993403239 created "2016-06-24" @default.
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- W1993403239 date "2012-03-01" @default.
- W1993403239 modified "2023-09-24" @default.
- W1993403239 title "Sentiment Classification Based on Random Process" @default.
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- W1993403239 doi "https://doi.org/10.1109/iccsee.2012.377" @default.
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