Advanced studies on traditional Chinese poetry style identification

Based on machine learning methods - naive Bayes, hill-climbing strategy and genetic algorithm, this paper proposes a traditional Chinese poetry style identification calculation improvement model to identify bold-and-unrestrained or graceful-and-restrained styles, that derive from machine learning Chinese classical Ci in Song Dynasty. Feature subset selection is performed based on genetic algorithm and has achieved satisfactory identification results in application. Additionally, this research project is supported by Chinese National Natural Science Fund (60173060).