| Title: | design of text categorization system based on svm |
| Author: | Liu Zhenyan
; Wang Weiping
; Wang Yong
|
| Source: | Advanced Materials Research
|
| Conference Name: | 2012 2nd International Conference on Materials Science and Information Technology, MSIT 2012
|
| Conference Date: | August 24, 2012 - August 26, 2012
|
| Issued Date: | 2012
|
| Conference Place: | Xi'an, Shaan, China
|
| Keyword: | Classification (of information)
; Feature extraction
; Image retrieval
; Information technology
; Materials science
; Text processing
|
| Indexed Type: | EI
|
| ISSN: | 1022-6680
|
| ISBN: | 9783037854389
|
| Department: | (1) Institute of Computing Technology Chinese Academy of Sciences China; (2) Graduate University Chinese Academy of Sciences China; (3) School of Software Beijing Institute of Technology China
|
| Abstract: | 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. |
| English Abstract: | 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. |
| Language: | 英语
|
| Content Type: | 会议论文
|
| URI: | http://ir.iscas.ac.cn/handle/311060/15957
|
| Appears in Collections: | 软件所图书馆_会议论文
|
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| Recommended Citation: | |
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.
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