Presentation | 1996/1/18 A Study on Relative Least General Generalization from Background Knowledge which includes Disjunction Ribou ONO, Naohiro ISHII, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, many methods of inductive learning which used the background knowledge have be studied. Relative least general generalization is one, in which the background knowledge is restricted to set of atoms (conjection). In this paper, we propose a method of extended relative least general generalization which includes disjunction expression in background knowledge to treat imperfect knowledge. When a problem can't be solved without disjunction knowledge, this extension is applied to it. A efficient computing method is also proposed. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | inductive learning / imperfect knowledge / disjunction knowledge |
Paper # | AI95-46 |
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Conference Information | |
Committee | AI |
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Conference Date | 1996/1/18(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Study on Relative Least General Generalization from Background Knowledge which includes Disjunction |
Sub Title (in English) | |
Keyword(1) | inductive learning |
Keyword(2) | imperfect knowledge |
Keyword(3) | disjunction knowledge |
1st Author's Name | Ribou ONO |
1st Author's Affiliation | Nagoya institute of Technology() |
2nd Author's Name | Naohiro ISHII |
2nd Author's Affiliation | Nagoya institute of Technology |
Date | 1996/1/18 |
Paper # | AI95-46 |
Volume (vol) | vol.95 |
Number (no) | 460 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |