| Presentation | 2000/7/12 Japanese Dependency Structure Analysis based on Support Vector Machine Taku Kudoh, Yuji Matsumoto, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper describes an analysis method of Japanese dependency structure based on Support Vector Machine(SVM). Conventional parsing techniques based on Machine Learning framework, such as Decision Tree and Maximum Entropy Model, cannot analyze sentence precisely, since features in these models must be selected carefully and it is difficult to train combination of features. On the other hand, it is well-known that SVM achieves high generalization performance even with high dimensional input data. Furthermore, by introducing the kernel principle, SVM can carry out the training in high-dimensional spaces with smaller computational cost independent of their dimensionality. We apply SVM to Japanese dependency structure identification problem. Experimental results on Kyoto University corpus show that our system performs 88.66% even with small training data(5540 sentences). |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Parsing / Dependency Structure Analysis / Machine Learning / Support Vector Machine |
| Paper # | NLC2000-20 |
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| Conference Information | |
| Committee | NLC |
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| Conference Date | 2000/7/12(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
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| Vice Chair | |
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| Paper Information | |
| 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) | Japanese Dependency Structure Analysis based on Support Vector Machine |
| Sub Title (in English) | |
| Keyword(1) | Parsing |
| Keyword(2) | Dependency Structure Analysis |
| Keyword(3) | Machine Learning |
| Keyword(4) | Support Vector Machine |
| 1st Author's Name | Taku Kudoh |
| 1st Author's Affiliation | Graduate School of Infomation Science, Nara Institute Science and Technology() |
| 2nd Author's Name | Yuji Matsumoto |
| 2nd Author's Affiliation | Graduate School of Infomation Science, Nara Institute Science and Technology |
| Date | 2000/7/12 |
| Paper # | NLC2000-20 |
| Volume (vol) | vol.100 |
| Number (no) | 201 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |