| 基于支持向量机的先秦诸子典籍自动分类研究 |
| |
| 引用本文： | 王东波,何琳,黄水清.基于支持向量机的先秦诸子典籍自动分类研究[J].图书情报工作,2017,61(12):71-76. |
| |
| 作者姓名： | 王东波 何琳 黄水清 |
| |
| 作者单位： | 1. 南京农业大学信息科学技术学院 南京 210095;
2. 南京农业大学领域知识关联研究中心 南京 210095 |
| |
| 基金项目： | 本文系国家社科基金重大项目"基于《汉学引得丛刊》的典籍知识库构建及人文计算研究"（项目编号：15ZDB127）、南京农业大学人文社科基金项目（项目编号：SKPT2016001）和国家社会科学基金青年项目"哈佛燕京学社汉学引得丛刊研究"（项目编号：12CTQ019）研究成果之一。 |
| |
| 摘 要： | 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。
|
| 关 键 词： | 先秦典籍 支持向量机 自动分类 古文信息处理 |
| 收稿时间： | 2017-02-13 |
Research of Automatic Classification for Pre-Qin Philosophers Literature Based on the Support Vector Machine |
| |
| Wang Dongbo,He Lin,Huang Shuiqing.Research of Automatic Classification for Pre-Qin Philosophers Literature Based on the Support Vector Machine[J].Library and Information Service,2017,61(12):71-76. |
| |
| Authors: | Wang Dongbo He Lin Huang Shuiqing |
| |
| Institution: | 1. College of Information Science and Technology, Nanjing Agricultural University, Nanjing 210095;
2. Research Center for Correlation of Domain Knowledge, Nanjing Agricultural University, Nanjing 210095 |
| |
| Abstract: | 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. |
| |
| Keywords: | Pre-Qin Literature support vector machine automatic classification ancient Chinese character information processing |
|
| 点击此处可从《图书情报工作》浏览原始摘要信息 |
| 点击此处可从《图书情报工作》下载免费的PDF全文 |
|
