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Title: 述語項構造解析による検索対象細分化を用いた自然文検索
Other Titles: Natural Language Search Based on Subdividing Objects of Search Using Predicate Argument Structure Analysis
Authors: 山田, 浩之1 Browse this author
ジェプカ, ラファウ2 Browse this author →KAKEN DB
荒木, 健治3 Browse this author →KAKEN DB
Authors(alt): YAMADA, Hiroyuki1
Rzepka, Rafal2
ARAKI, Kenji3
Keywords: Natural language query
Information Retrieval
judicial precedents extraction
Issue Date: 20-Jan-2011
Publisher: 一般社団法人電子情報通信学会
Journal Title: 電子情報通信学会技術研究報告. NLC, 言語理解とコミュニケーション
Volume: 110
Issue: 400
Start Page: 59
End Page: 64
Abstract: 本手法では,述語項構造解析を用いて,自然言語文で表現されたクエリに含まれる単語,係り受け関係に対して,項構造によるスコア付与を行い,データベースからの検索を行った.特に,述語項構造解析によって「ガ格」として判別された単語に対して,検索文章中で主となる「検索主体」を定義することによって検索を行う.これにより,単語によるスコアの偏りによる問題が是正できる.述語項構造解析にはSynChaを用い,実験では交通事故の判例,「教えて!goo」のテキストを対象とした.
In this paper we describe our system for retrieving texts using predicate argument structure analysis for queries in natural language. A dependency relation included in a query decides a word score, which is retrieved by defining "retrieval subject" that further becomes the main clue for retrieving sentences using a word classified by predicate argument structure analysis tool SynCha as "-ga case". As a result, the problem of biased word score can be corrected. In this research we target judicial precedents of traffic accidents and use "Oshiete! goo" online QA community entries for experiments.
Rights: Copyright©2011 IEICE
Type: article
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: RZEPKA Rafal

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