Presentation | 2006-01-12 Realization of Text Classification Systems by Approximation of Classification Functions based on the Genetic Programming and its Applications Noboru TAKAGI, Shozo TOKINAGA, |
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Abstract(in English) | This paper deals with the realization of text classification systems by using sequence estimation of words and approximation of classification functions based on the Genetic Programming (GP) and its Applications. Conventional text classification methods utilize the feature vector corresponding to frequecy of appearance of key-words, but the method can not provide us sufficient results. In the paper, we apply the GP procedure to approximate nonlinear classification functions in which the elements of feature vector are used for the input variables. The method of the paper is applied to simulation studies for artificially generated text, and also to theclassification of real article in the field of economics. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Rule estimation / Genetic Programming / categorization |
Paper # | CAS2005-77 |
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Committee | CAS |
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Conference Date | 2006/1/5(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Circuits and Systems (CAS) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Realization of Text Classification Systems by Approximation of Classification Functions based on the Genetic Programming and its Applications |
Sub Title (in English) | |
Keyword(1) | Rule estimation |
Keyword(2) | Genetic Programming |
Keyword(3) | categorization |
1st Author's Name | Noboru TAKAGI |
1st Author's Affiliation | Dept. of Management and Infomation Science, Nagasaki Institute of Applied Science First University() |
2nd Author's Name | Shozo TOKINAGA |
2nd Author's Affiliation | Graduate School of Economics, Kyushu Univ. |
Date | 2006-01-12 |
Paper # | CAS2005-77 |
Volume (vol) | vol.105 |
Number (no) | 503 |
Page | pp.pp.- |
#Pages | 5 |
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