Presentation | 2003/10/30 On Selection Criteria of Combinatorial Features for Machine Learning(Natural Language Understanding and Models of Communication) Hideki ISOZAKI, Tsutomu HIRAO, Jun SUZUKI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Machine Learning is used for various tasks of Natural Language Processing such as Named Entity Recognition, Important Sentence Extraction, and Dependency Analysis. Features for Machine Learning are found by trial and error. However, it is possible to find useful features by using statistical measures. For example, PrefixSpan finds frequent word patterns and TidalSMP finds useful feature combinations. Such combinatiorial features are often redundant and are not optimized for Machine Learning. Here, we show that a simple reranking method improves the performance of Machine Learning in two tasks: Important Sentence Extraction and English Dependency Analysis. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | PrefixSpan / TidalSMP / SVM / Feature Selection / Machine Learning / Mining |
Paper # | NLC2003-34 |
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Committee | NLC |
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Conference Date | 2003/10/30(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | On Selection Criteria of Combinatorial Features for Machine Learning(Natural Language Understanding and Models of Communication) |
Sub Title (in English) | |
Keyword(1) | PrefixSpan |
Keyword(2) | TidalSMP |
Keyword(3) | SVM |
Keyword(4) | Feature Selection |
Keyword(5) | Machine Learning |
Keyword(6) | Mining |
1st Author's Name | Hideki ISOZAKI |
1st Author's Affiliation | NTT Communication Science Laboratories, NTT Corporation() |
2nd Author's Name | Tsutomu HIRAO |
2nd Author's Affiliation | NTT Communication Science Laboratories, NTT Corporation |
3rd Author's Name | Jun SUZUKI |
3rd Author's Affiliation | NTT Communication Science Laboratories, NTT Corporation |
Date | 2003/10/30 |
Paper # | NLC2003-34 |
Volume (vol) | vol.103 |
Number (no) | 407 |
Page | pp.pp.- |
#Pages | 6 |
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