Presentation	2001/7/10 Japanese case analysis based on a machine learning method that uses borrowed supervised data Masaki Murata,
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Abstract(in Japanese)	(See Japanese page)
Abstract(in English)	We have developed a new machine learning method that uses borrowed supervised data. In this method, supervised data is borrowed from corpola that do not have annotated tags related to the problems we are currently trying to solve. We have also developed a new machine learning method that uses both supervised data received from corpola that have annotated tags related to the problems we are currently addressing and borrowed supervised data that does not have those annotated tags. These methods can both be used with any type of ellipsis resolution. In this paper, we will show how these methods can be applied to Japanese case analysis as well as confirm their effectiveness.
Keyword(in Japanese)	(See Japanese page)
Keyword(in English)	Machine Learning / Case Analysis / Type Borrowing Supervised Data / Ellipsis Resoulution
Paper #	NLC2001-24
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Conference Information
Committee	NLC
Conference Date	2001/7/10(1days)
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Paper Information
Registration To	Natural Language Understanding and Models of Communication (NLC)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Japanese case analysis based on a machine learning method that uses borrowed supervised data
Sub Title (in English)
Keyword(1)	Machine Learning
Keyword(2)	Case Analysis
Keyword(3)	Type Borrowing Supervised Data
Keyword(4)	Ellipsis Resoulution
1st Author's Name	Masaki Murata
1st Author's Affiliation	Keihanna Human Info-communication Research Center, Communications Research Laboratory()
Date	2001/7/10
Paper #	NLC2001-24
Volume (vol)	vol.101
Number (no)	190
Page	pp.pp.-
#Pages	8
Date of Issue