Presentation 1998/1/22
Grammatical Inference for Concept Acquisition from Documents.
Kenji Hanakawa, Hideaki Takeda, Toyoaki Nishida,
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Abstract(in English) The purpose of this study is to acquire knowledge from large scale natural language documents. There are two types of knowledge in the documents. One is explicitly represented knowledge which is acquired using natural language processing. The other is implicit constraint. In this paper, how to acquire implicit constraint using grammatical inference from the documents is described. We propose a grammatical inference system which uses inference rules based on logic, and show that the system can learn easy pattern of character lists. We also discuss its application to knowledge acquisition from real documents.
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Keyword(in English) grammatical inference / knowledge acquisition / logic programming / concept learning
Paper # KBSE97-26
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Committee KBSE
Conference Date 1998/1/22(1days)
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Registration To Knowledge-Based Software Engineering (KBSE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Grammatical Inference for Concept Acquisition from Documents.
Sub Title (in English)
Keyword(1) grammatical inference
Keyword(2) knowledge acquisition
Keyword(3) logic programming
Keyword(4) concept learning
1st Author's Name Kenji Hanakawa
1st Author's Affiliation Department of Electrical Engineering and Computer Science, Osaka Prefectural College of Technology()
2nd Author's Name Hideaki Takeda
2nd Author's Affiliation Graduate School of Information Science and Technology, Nara Institute of Science and Technology
3rd Author's Name Toyoaki Nishida
3rd Author's Affiliation Graduate School of Information Science and Technology, Nara Institute of Science and Technology
Date 1998/1/22
Paper # KBSE97-26
Volume (vol) vol.97
Number (no) 502
Page pp.pp.-
#Pages 6
Date of Issue