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| 支持向量机在网页信息分类中的应用研究 | |
| 引用本文： | 刘丽珍,贺海军,陆玉昌,宋瀚涛.支持向量机在网页信息分类中的应用研究[J].小型微型计算机系统,2007,28(2):337-340. |
| 作者姓名： | 刘丽珍 贺海军 陆玉昌 宋瀚涛 |
| 作者单位： | 1. 首都师范大学,信息工程学院,北京,100037 2. 北京中搜在线软件有限公司,北京,100044 3. 清华大学,计算机系,北京,100084 4. 北京理工大学,计算机系,北京,100081 |
| 基金项目： | 国家重点基础研究发展计划(973计划);北京市教委科技发展计划项目;北京市优秀人才专项经费项目 |
| 摘 要： | 针对日益膨胀的网络信息,为方便用户准确定位所需的信息,将支持向量机(SVM)与二叉决策树结合起来进行网页信息的分类,并在构造决策支持向量机分类模型的基础上,进一步结合聚类的方法,解决多类分类问题,减少支持向量机的训练样本数,提高分类训练速度和分类准确率. |
| 关 键 词： | 支持向量机 决策树 网页分类 |
| 文章编号： | 1000-1220（2007）02-0337-04 |
| 修稿时间： | 2005-11-16 |
Application Research of Support Vector Machine in Web Information Classification |
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| LIU Li-zhen,HE Hai-jun,LU Yu-chang,SONG Han-tao.Application Research of Support Vector Machine in Web Information Classification[J].Mini-micro Systems,2007,28(2):337-340. | |
| Authors: | LIU Li-zhen HE Hai-jun LU Yu-chang SONG Han-tao |
| Affiliation: | 1 Information Engineering College, Capital Normal University, Beijing 100037, China ; 2 Beijing Zhongsou Online Software Corporation, Beijing 100044, China; 3 Department of Computer , Tsinghua University, Beijing 100084, China; 4 Department of Computer, Beijing Institute of Technology, Beijing 100081, China |
| Abstract: | Information retrieval is facing great challenge due to the explosion of the network scales. This makes more researchers focus on the issue of Web page classification technology. To facilitating user accurately locating information needed, applying binary decision tree into Support Vector Machine (SVM), a new SVM method based Web information classification algorithm has been introduced. Based on classifier composed by SVM-Decision Tree, a proposed approach was supported by the clustering method to solve the multi-category classification problem, reduces numbers of the training sample in SVM, and increases the classification speed and accuracy effectively. |
| Keywords: | SVM decision tree web classification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |