基于支持向量机的先秦诸子典籍自动分类研究

Research of Automatic Classification for Pre-Qin Philosophers Literature Based on the Support Vector Machine

[目的 /意义]在人文计算兴起这一背景下,针对先秦诸子典籍进行自动分类的探究,以更加深入和精准地从古代典籍中挖掘出相应的知识。[方法 /过程]基于《论语》《老子》《管子》《庄子》《孙子》《韩非子》《孟子》《荀子》和《墨子》9种先秦诸子典籍构成的训练和测试语料,采用支持向量机技术,提取TF-IDF、信息增益、卡方统计和互信息为特征,完成针对先秦诸子典籍的自动分类实验。[结果 /结论]基于先秦诸子典籍得到的自动分类模型调和平均值能达到99.21%,效果较好,具有较强的推广和应用价值。

：[Purpose/significance] In order to deeply and accurately mine the knowledge from the ancient classics, the automatic classification of Pre-Qin Literature is implemented at the background of the rising of humanities computing. [Method/process] Based on the training and testing corpus which consisted of 9 kinds of full texts of the Analects of Confucius, Laozi, Guanzi, Zhuangzi, Xunzi, Han Fei Zi, Mencius, Xunzi and Mozi, the paper finished experiments about the automatic classification of Pre-Qin Philosophers Literature by the support vector machine which used the feature selection, which included TF-IDF, information gain, Chi-square statistics and mutual information determined by the method of statistics rules. [Result/conclusion] The classification models based on the support vector machine are obtained under 4 different feature selection methods for Pre-Qin Philosophers Literature. The best F-measure of classification model reaches 99.21% which has favorable effect and the value of promotion and application.