An automatic sameAs link discovery from Wikipedia

Kosuke Kagawa, Susumu Tamagawa, Takahira Yamaguchi

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Spelling variants of words or word sense ambiguity takes many costs in such processes as Data Integration, Information Searching, data pre-processing for Data Mining, and so on. It is useful to construct relations between a word or phrases and a representative name of the entity to meet these demands. To reduce the costs, this paper discusses how to automatically discover "sameAs" and "meaningOf" links from Japanese Wikipedia. In order to do so, we gathered relevant features such as IDF, string similarity, number of hypernym, and so on. We have identified the link-based score on salient features based on SVM results with 960,000 anchor link pairs. These case studies show us that our link discovery method goes well with more than 70% precision/ recall rate.

本文言語English
ホスト出版物のタイトルSemantic Technology - Third Joint International Conference, JIST 2013, Revised Selected Papers
出版社Springer Verlag
ページ399-413
ページ数15
ISBN(印刷版)9783319068251
DOI
出版ステータスPublished - 2014 1 1
イベント3rd Joint International Semantic Technology Conference, JIST 2013 - Seoul, Korea, Republic of
継続期間: 2013 11 282013 11 30

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)
8388 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other3rd Joint International Semantic Technology Conference, JIST 2013
CountryKorea, Republic of
CitySeoul
Period13/11/2813/11/30

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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