JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
A Novel Statistical Feature Selection Approach for Text Categorization |
| 영문제목(English Title) |
A Novel Statistical Feature Selection Approach for Text Categorization |
| 저자(Author) |
Mohamed Abdel Fattah
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| 원문수록처(Citation) |
VOL 13 NO. 05 PP. 1397 ~ 1409 (2017. 10) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
For text categorization task, distinctive text features selection is important due to feature space high dimensionality. It is important to decrease the feature space dimension to decrease processing time and increase accuracy. In the current study, for text categorization task, we introduce a novel statistical feature selection approach. This approach measures the term distribution in all collection documents, the term distribution in a certain category and the term distribution in a certain class relative to other classes. The proposed method results show its superiority over the traditional feature selection methods. |
| 키워드(Keyword) |
Electronic Texts
E-mail Filtering
Feature Select
SMS Spam Filtering
Text Categorization
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| 파일첨부 |
PDF 다운로드
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