Presentation | 2012-11-07 A Proposal of Adaptive Metric Learning Using Category Information for Text Classification Kenta MIKAWA, Takashi ISHIDA, Masayuki GOTO, Shigeichi HIRASAWA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Extended cosine measure has been proposed as one of the method of metric learning which learns metric matrix expressing the characteristics of training data. However, this method introduces a unique metric matrix and estimate it by learning of all training data. Therefore, there is a room to improve this method because document data has normally different statistical characteristics in each category. In this study, we propose the way of learning metric matrices for each category. To show the effectiveness of our proposed method, simulation experiment is conducted. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Metric Learning / Extended Cosine Measure / Vector Space Model / Text Classification |
Paper # | IBISML2012-45 |
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Committee | IBISML |
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Conference Date | 2012/10/31(1days) |
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Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Proposal of Adaptive Metric Learning Using Category Information for Text Classification |
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Keyword(1) | Metric Learning |
Keyword(2) | Extended Cosine Measure |
Keyword(3) | Vector Space Model |
Keyword(4) | Text Classification |
1st Author's Name | Kenta MIKAWA |
1st Author's Affiliation | Graduate School of Creative Science and Engineering, Waseda University() |
2nd Author's Name | Takashi ISHIDA |
2nd Author's Affiliation | Madia Network Center, Waseda University |
3rd Author's Name | Masayuki GOTO |
3rd Author's Affiliation | School of Creative Science and Engineering, Waseda University |
4th Author's Name | Shigeichi HIRASAWA |
4th Author's Affiliation | Research Institute for Science and Engineering, Waseda University |
Date | 2012-11-07 |
Paper # | IBISML2012-45 |
Volume (vol) | vol.112 |
Number (no) | 279 |
Page | pp.pp.- |
#Pages | 6 |
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