Using graph based method to improve bootstrapping relation extraction

Haibo Li*, Danushka Bollegala, Yutaka Matsuo, Mitsuru Ishizuka

*この研究の対応する著者

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

Many bootstrapping relation extraction systems processing large corpus or working on the Web have been proposed in the literature. These systems usually return a large amount of extracted relationship instances as an out-of-ordered set. However, the returned result set often contains many irrelevant or weakly related instances. Ordering the extracted examples by their relevance to the given seeds is helpful to filter out irrelevant instances. Furthermore, ranking the extracted examples makes the selection of most similar instance easier. In this paper, we use a graph based method to rank the returned relation instances of a bootstrapping relation extraction system. We compare the used algorithm to the existing methods, relevant score based methods and frequency based methods, the results indicate that the proposed algorithm can improve the performance of the bootstrapping relation extraction systems.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ127-138
ページ数12
6609 LNCS
PART 2
DOI
出版ステータスPublished - 2011
外部発表はい
イベント12th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2011 - Tokyo
継続期間: 2011 2 202011 2 26

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 2
6609 LNCS
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other12th International Conference on Computational Linguistics and Intelligent Text Processing, CICLing 2011
CityTokyo
Period11/2/2011/2/26

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 理論的コンピュータサイエンス

フィンガープリント

「Using graph based method to improve bootstrapping relation extraction」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル