Suggesting specific segments as link targets in Wikipedia

Renzhi Wang, Mizuho Iwaihara

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Wikipedia is the largest online encyclopedia, in which articles form knowledgeable and semantic resources. Links within Wikipedia indicate that the two texts of a link origin and destination are related about their semantic topics. Existing link detection methods focus on article titles because most of links in Wikipedia point to article titles. But there are a number of links in Wikipedia pointing to corresponding segments, because the whole article is too general and it is hard for readers to obtain the intention of the link. We propose a method to automatically predict whether a link target is a specific segment and provide which segment is most relevant. We propose a combination method of Latent Dirichlet Allocation (LDA) and Maximum Likelihood Estimation (MLE) to represent every segment as a vector, then we obtain similarity of each segment pair, finally we utilize variance, standard deviation and other statistical features to predict the results. Through evaluations on Wikipedia articles, our method performs better result than existing methods.

本文言語English
ホスト出版物のタイトルDigital Libraries
ホスト出版物のサブタイトルKnowledge, Information, and Data in an Open Access Society - 18th International Conference on Asia-Pacific Digital Libraries, ICADL 2016, Proceedings
編集者Atsuyuki Morishima, Andreas Rauber, Chern li Liew
出版社Springer Verlag
ページ394-405
ページ数12
ISBN(印刷版)9783319493039
DOI
出版ステータスPublished - 2016 1 1
イベント18th International Conference on Asia-Pacific Digital Libraries, ICADL 2016 - Tsukuba, Japan
継続期間: 2016 12 72016 12 9

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)
10075 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other18th International Conference on Asia-Pacific Digital Libraries, ICADL 2016
CountryJapan
CityTsukuba
Period16/12/716/12/9

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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