LearningWeb query patterns for imitatingWikipedia articles

Shohei Tanaka, Naokaki Okazaki, Mitsuru Ishizuka

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This paper presents a novel method for acquiring a set of query patterns to retrieve documents containing important information about an entity. Given an existing Wikipedia category that contains the target entity, we extract and select a small set of query patterns by presuming that formulating search queries with these patterns optimizes the overall precision and coverage of the returned Web information. We model this optimization problem as a weighted maximum satisfiability (weighted Max-SAT) problem. The experimental results demonstrate that the proposed method outperforms other methods based on statistical measures such as frequency and point-wise mutual information (PMI), which are widely used in relation extraction.

本文言語English
ホスト出版物のタイトルColing 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference
ページ1229-1237
ページ数9
2
出版ステータスPublished - 2010
外部発表はい
イベント23rd International Conference on Computational Linguistics, Coling 2010 - Beijing
継続期間: 2010 8 232010 8 27

Other

Other23rd International Conference on Computational Linguistics, Coling 2010
CityBeijing
Period10/8/2310/8/27

ASJC Scopus subject areas

  • Language and Linguistics
  • Computational Theory and Mathematics
  • Linguistics and Language

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