Presentation | 1998/5/15 Automatic Generation of Dependency Rules for Japanese Noun Phrases with Particles"no" Shinji NAKAI, Satoru IKEHARA, Satoshi SHIRAI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper proposed a method automatically to generate dependency rules for "A no B no C", the most typical noun phrases and frequently appeared in Japanese (similar to "C of B of A" in English), using a semantic attribute system currently developed. In this method, 3 kinds of semantic dependency rules such as one-, two-, tree-dimensional rules are independently generated from a noun phrase data-base. In the experiments, the generated rules were applied to the dependency analysis (in the order of 1-, 2- and 3-dimensional rules) resulting in the recall rate of 96.0%, precision rate of 88.4%, accuracy rate of 85.1%.From these result, it was found that the method yields accurate rules for dependency analysis. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Noun Analysis / Dependency Rule / Machine Learning / Generalization |
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Committee | NLC |
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Conference Date | 1998/5/15(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (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) | Automatic Generation of Dependency Rules for Japanese Noun Phrases with Particles"no" |
Sub Title (in English) | |
Keyword(1) | Noun Analysis |
Keyword(2) | Dependency Rule |
Keyword(3) | Machine Learning |
Keyword(4) | Generalization |
1st Author's Name | Shinji NAKAI |
1st Author's Affiliation | Faculty of Engineering, Tottori University() |
2nd Author's Name | Satoru IKEHARA |
2nd Author's Affiliation | Faculty of Engineering, Tottori University |
3rd Author's Name | Satoshi SHIRAI |
3rd Author's Affiliation | NTT Communication Science Laboratories |
Date | 1998/5/15 |
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Volume (vol) | vol.98 |
Number (no) | 53 |
Page | pp.pp.- |
#Pages | 8 |
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