期刊
INFORMATION AND SOFTWARE TECHNOLOGIES, ICIST 2018
卷 920, 期 -, 页码 227-239出版社
SPRINGER-VERLAG BERLIN
DOI: 10.1007/978-3-319-99972-2_18
关键词
SVM; Big data arrays; Sentiment analysis
SVM technique is one of the best techniques to classify data, but it has a slow performance in the big data arrays. This paper introduces the method to improve the speed of SVM classification in sentiment analysis by reducing the training set. The method was tested on the Stanford Twitter sentiment corpus dataset and Amazon customer reviews dataset. The results show that the execution time of the introduced method outperforms the standard SVM classification method.
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