| 基于SVM的大容量网页的分类研究 |
| |
| 引用本文： | 张越,曹文君.基于SVM的大容量网页的分类研究[J].计算机应用与软件,2008,25(9). |
| |
| 作者姓名： | 张越 曹文君 |
| |
| 作者单位： | 复旦大学计算机与信息技术系,上海,200433 |
| |
| 摘 要： | 对从噪音信息中辨别有用的信息这一问题提出了一种解决方法.将大型的样本空间分解到可变的变量集和固定的变量集,并且让可变的变量集成为"工作集",使大型样本空间转变为小型的空间,然后引用primal-dual interior-point-solver来解决问题.
|
| 关 键 词： | 支持向量机 二次优化问题 特征选择 网络爬虫 |
CLASSIFICATION OF LARGE-SCALE WEB PAGES BASED ON SVM |
| |
| Zhang Yue,Cao Wenjun.CLASSIFICATION OF LARGE-SCALE WEB PAGES BASED ON SVM[J].Computer Applications and Software,2008,25(9). |
| |
| Authors: | Zhang Yue Cao Wenjun |
| |
| Affiliation: | Zhang Yue Cao Wenjun(Department of Computing , Information Technology,Fudan University,Shanghai 200433,China) |
| |
| Abstract: | A solution is proposed to tell the useful information from the noisy information.The large example space is decomposed into free variable set and fixed variable set,and the free variable set is made become the working set,which converts the large example space into a smaller one.Then,primal-dual interior-point-solver is applied to solve the problem. |
| |
| Keywords: | Support vector machine Quadratic optimization problem Feature selection Web spider |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
