Abstract
We proposed a text classification model for classical Chinese lyrics and songs in this paper. 596 Song lyrics and Yuan songs are represented in vectors with Vector Space Model. The classifiers are based on Naive Bayes and Support Vector Machine algorithms, which both performed well in the experiment (with SVM, the F-measure up to 92.6%). In addition, we examined the performance of the classifiers in sorting atypical texts, with lyrics and songs in Ming dynasty as the test set. Although the F-measure drops to 79.2%, it still demonstrates stylistic changes in lyrics in Ming dynasty.
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