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 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.
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Keyword(in English) inductive learning / imperfect knowledge / disjunction knowledge
Paper # AI95-46
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Conference Information
Committee AI
Conference Date 1996/1/18(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
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