Abstract
The category of subjective aesthetic was distinguished into automatic text categorization of natural language processing problem. The Song dynasty poems were collected and randomly divided into training set and testing set based on keyword features. Three classification methods, which are K-nearest neighbor, naive Bayes classifier and support vector machine, were used to classify the poems’ genres. Results showed that support vector machine can classify best and achieved above 95% accuracy.
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© 2015 Springer International Publishing Switzerland
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Mu, Y. (2015). Using Keyword Features to Automatically Classify Genre of Song Ci Poem. In: Lu, Q., Gao, H. (eds) Chinese Lexical Semantics. CLSW 2015. Lecture Notes in Computer Science(), vol 9332. Springer, Cham. https://doi.org/10.1007/978-3-319-27194-1_48
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DOI: https://doi.org/10.1007/978-3-319-27194-1_48
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