Presentation | 2000/7/12 Data Mining of Sentence Structures using Relative Indexing of Vertices Mayumi OYAMA, Takashi OKADA, Shigeki KUROSAKI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Data mining deals with the discovery of hidden knowledge, unexpected patterns and new rules from large databases. Corpuses are large databases and text-mining techniques are making rapid progress. If we apply the technique of data mining to discover knowledge in corpuses, we will get good results. But, to analyze corpuses with syntactic parse trees we have to treat their structures. In this paper, we show the inscription of syntactic parse tree first and we propose the data mining methods using the relative indexing of vertices for knowledge discover from corpuses. We show the distinctive structural features found between an intransitive verb"think"and a transitive verb"think". |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | data mining / relative indexing / syntactic parse tree / knowledge discovery |
Paper # | NLC2000-19 |
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Committee | NLC |
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Conference Date | 2000/7/12(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) | Data Mining of Sentence Structures using Relative Indexing of Vertices |
Sub Title (in English) | |
Keyword(1) | data mining |
Keyword(2) | relative indexing |
Keyword(3) | syntactic parse tree |
Keyword(4) | knowledge discovery |
1st Author's Name | Mayumi OYAMA |
1st Author's Affiliation | Center for Information & Media Studies, Kwansei Gakuin University() |
2nd Author's Name | Takashi OKADA |
2nd Author's Affiliation | Center for Information & Media Studies, Kwansei Gakuin University |
3rd Author's Name | Shigeki KUROSAKI |
3rd Author's Affiliation | Center for Information & Media Studies, Kwansei Gakuin University |
Date | 2000/7/12 |
Paper # | NLC2000-19 |
Volume (vol) | vol.100 |
Number (no) | 201 |
Page | pp.pp.- |
#Pages | 8 |
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