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Advanced studies on traditional Chinese poetry style identification

机译:中国传统诗词风格识别研究

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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).
机译:基于朴素贝叶斯,爬山策略和遗传算法等机器学习方法,提出了一种传统的中国诗歌风格识别计算改进模型,用于识别源自机器学习汉语的粗体和不受约束的风格。宋代的古典词。基于遗传算法进行特征子集选择,在应用中取得了令人满意的识别结果。此外,该研究项目还获得了中国国家自然科学基金(60173060)的资助。

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