摘要
本文对诗词采用向量空间模型来表示,基于机器学习中的朴素贝叶斯等方法,首次提出了古典诗词的豪放和婉约风格判别计算模型,并用遗传算法对模型进行改进,取得较好的诗词风格判别结果。该模型已经在精典诗词语料的机器学习基础上得以实现,并且获得较好的诗词风格判别效果。
Based on Machine Learning methods--Nalve Bayes and Genetic Algorithm, this paper proposes a Tradi- tional Chinese Poetry Style Identification Calculation Improvement Model to identify Bold-and-Unrestrained or Grace- ful-and-Restrained styles, that derive from Machine Learning Chinese Classical Ci in Song Dynasty. Feature subset se- lection is performed based on Genetic Algorithm and has achieved satisfactory identification results in application.
出处
《计算机科学》
CSCD
北大核心
2005年第7期156-158,共3页
Computer Science
基金
国家自然科学基金(基金号60173060)
