design of text categorization system based on svm
文献类型：会议论文
| 作者 | Liu Zhenyan ; Wang Weiping ; Wang Yong |
| 出版日期 | 2012 |
| 会议名称 | 2012 2nd International Conference on Materials Science and Information Technology, MSIT 2012 |
| 会议日期 | August 24, 2012 - August 26, 2012 |
| 会议地点 | Xi'an, Shaan, China |
| 关键词 | Classification (of information) Feature extraction Image retrieval Information technology Materials science Text processing |
| 页码 | 1191-1195 |
| 中文摘要 | This paper introduces the design of a text categorization system based on Support Vector Machine (SVM). It analyzes the high dimensional characteristic of text data, the reason why SVM is suitable for text categorization. According to system data flow this system is constructed. This system consists of three subsystems which are text representation, classifier training and text classification. The core of this system is the classifier training, but text representation directly influences the currency of classifier and the performance of the system. Text feature vector space can be built by different kinds of feature selection and feature extraction methods. No research can indicate which one is the best method, so many feature selection and feature extraction methods are all developed in this system. For a specific classification task every feature selection method and every feature extraction method will be tested, and then a set of the best methods will be adopted. © (2012) Trans Tech Publications, Switzerland. |
| 英文摘要 | This paper introduces the design of a text categorization system based on Support Vector Machine (SVM). It analyzes the high dimensional characteristic of text data, the reason why SVM is suitable for text categorization. According to system data flow this system is constructed. This system consists of three subsystems which are text representation, classifier training and text classification. The core of this system is the classifier training, but text representation directly influences the currency of classifier and the performance of the system. Text feature vector space can be built by different kinds of feature selection and feature extraction methods. No research can indicate which one is the best method, so many feature selection and feature extraction methods are all developed in this system. For a specific classification task every feature selection method and every feature extraction method will be tested, and then a set of the best methods will be adopted. © (2012) Trans Tech Publications, Switzerland. |
| 收录类别 | EI |
| 会议录 | Advanced Materials Research
 |
| 语种 | 英语 |
| ISSN号 | 1022-6680 |
| ISBN号 | 9783037854389 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15957]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Liu Zhenyan,Wang Weiping,Wang Yong. design of text categorization system based on svm[C]. 见:2012 2nd International Conference on Materials Science and Information Technology, MSIT 2012. Xi'an, Shaan, China. August 24, 2012 - August 26, 2012. |
入库方式： OAI收割
来源：软件研究所
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