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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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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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