Presentation 2015-02-05
Class-Instance Acquisition using Automatically Extracted Hyponymy Relations
Ichiro YAMADA, Taro MIYAZAKI, Masaru MIYAZAKI, Kikuka MIURA, Atsushi MATSUI, Hideki TANAKA,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Class-instance relation is useful for information extraction from large volume of text. For example, we can determine which medicine is effective for a sickness by co-occurrence information of instances of medicine and sickness. It is possible to acquire instances of a class from a legacy thesaurus but sufficient amount of instance is not registered in such extracted from Wikipedia and contain some error relations. We can acquire a large volume of instances with higher accuracy by using two kinds of noise reduction approaches. We report a semantic relation acquisition using automatically extracted class-instance relations.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Class-instance acquisition / hyponymy relation / semantic relation of words
Paper # NLC2014-44
Date of Issue

Conference Information
Committee NLC
Conference Date 2015/1/29(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

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) Class-Instance Acquisition using Automatically Extracted Hyponymy Relations
Sub Title (in English)
Keyword(1) Class-instance acquisition
Keyword(2) hyponymy relation
Keyword(3) semantic relation of words
1st Author's Name Ichiro YAMADA
1st Author's Affiliation Science and Technology Research Laboratories, Japan Broadcasting Corporation()
2nd Author's Name Taro MIYAZAKI
2nd Author's Affiliation Science and Technology Research Laboratories, Japan Broadcasting Corporation
3rd Author's Name Masaru MIYAZAKI
3rd Author's Affiliation Science and Technology Research Laboratories, Japan Broadcasting Corporation
4th Author's Name Kikuka MIURA
4th Author's Affiliation Science and Technology Research Laboratories, Japan Broadcasting Corporation
5th Author's Name Atsushi MATSUI
5th Author's Affiliation Science and Technology Research Laboratories, Japan Broadcasting Corporation
6th Author's Name Hideki TANAKA
6th Author's Affiliation Science and Technology Research Laboratories, Japan Broadcasting Corporation
Date 2015-02-05
Paper # NLC2014-44
Volume (vol) vol.114
Number (no) 444
Page pp.pp.-
#Pages 6
Date of Issue