Position: Home > Articles > Research of Algorithm of Chinese Verb Phrases Categorization Based on Support Vector Machine
Journal of Hebei North University(Natural Science Edition)
2008,24
(2)
66-70
基于SVM的汉语动词短语分类算法研究
作 者：
曹建芳;王鸿斌
单 位：
忻州师范学院计算机系
关键词：
动词短语分类;特征提取;向量空间模型
摘 要：
对SVM分类器进行了分析,提取了汉语动词短语的静态特征和动态特征,构造了动词短语的向量空间模型,提出了基于SVM的汉语动词短语分类算法.实验表明:与基于规则的分类方法比较,SVM方法大大减少分类器更新所需要的学习步骤和时间,是一种较好的分类算法.
译 名：
Research of Algorithm of Chinese Verb Phrases Categorization Based on Support Vector Machine
作 者：
CAO Jian-fang,WANG Hong-bin(Computer Department,Xinzhou Teachers' College,Xinzhou 034000,Shanxi,China)
关键词：
verb phrases categorization;feature drawing;vector space model
摘 要：
The SVM categorization model is analyzed,static and dynamic characteristic on Chinese verb phrase is extracted,vector space model on verb phrase is built,and an algorithm to perform Chinese verb phrases categorization using support vector machine is presented.Experiments show that the SVM model dramatically reduces the training time and steps and is a better classification algorithm.
导出引用
计量
文章访问数: 6
HTML全文浏览量: 0
PDF下载量: 0
所属期刊
