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- W2000720391 abstract "Sentiment categorization have been widely explored in many fields, such as government policy, information monitoring, product tracking, etc. This paper adopts k-NN, Naive Bayes and SVM classifiers to categorize sentiments contained in on-line Chinese reviews on digital products. Our experimental results show that combining the words and phrases with sentiment orientation as hybrid features, SWM classifier achieves an accuracy of 96,47%, which is words of all parts of speech as features." @default.
- W2000720391 created "2016-06-24" @default.
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- W2000720391 date "2010-08-01" @default.
- W2000720391 modified "2023-09-22" @default.
- W2000720391 title "Application of Chinese sentiment categorization to digital products reviews" @default.
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- W2000720391 doi "https://doi.org/10.1109/nlpke.2010.5587788" @default.
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