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General Information
    • ISSN: 2382-6185
    • Frequency: Quarterly (2015-2016); semiyearly (Since 2017)
    • DOI: 10.18178/IJKE
    • Editor-in-Chief: Prof. Chen-Huei Chou
    • Executive Editor: Ms. Nina Lee
    • Indexed by: Google Scholar, DOAJ, Engineering & Technology Digital Library, Crossref, ProQuest
    • E-mail: ijke@ejournal.net
Editor-in-chief
Prof. Chen-Huei Chou
College of Charleston, SC, USA
It is my honor to be the editor-in-chief of IJKE. I will do my best to help develop this journal better.
IJKE 2016 Vol.2(3): 122-127 ISSN: 2382-6185
doi: 10.18178/ijke.2016.2.3.065

A Japanese-Chinese Cross-Language Entity Linking Method with Entity Disambiguation Based on Document Similarity

Xiang Song, Jialiang Zhou, Fuminori Kimura, and Akira Maeda
Abstract—In this paper, we propose a method to automatically discover links between valuable keyphrases in a Japanese document and corresponding Chinese encyclopedia pages. The proposed method has three stages. First, we translate Japanese keyphrases into Chinese using a combination of three translation methods. Second, we extract all Chinese encyclopedia articles of the translated keyphrases. Third, we translate the original Japanese document into Chinese and make a vector of noun frequencies. We calculate the cosine similarities of original articles and all candidate Chinese encyclopedia ones. To find the appropriateness of term description pages for disambiguation, we make a rank with cosine similarity by comparing a Japanese document with Chinese encyclopedia articles. Finally, we add a link from a Japanese keyphrase to top-ranking Chinese encyclopedia article. In this paper, we use Wikipedia and Baidu Baike (an online encyclopedia published by Baidu, a Chinese search engine) articles to conduct our experiment. Although we achieved an accuracy rate of 81% by using Wikipedia, we achieved an accuracy rate of 97% by using Baidu Baike.

Index Terms—Encyclopedia, cross-language link discovery, Wikification, Baidu Baike.

Xiang Song and Jialiang Zhou are with the Graduate School of Information Science and Engineering, Ritsumeikan University, Shiga, Japan (e-mail: gr0187xx@ed.ritsumei.ac.jp, is0095hx@ed.ritsumei.ac.jp).
Fuminori Kimura is with the Faculty of Economics Management and Information Science, Onomichi City University, Hiroshima, Japan (e-mail: f-kimura@onomichi-u.ac.jp).
Akira Maeda is with the College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan (e-mail: amaeda@is.ritsumei.ac.jp).

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Cite: Xiang Song, Jialiang Zhou, Fuminori Kimura, and Akira Maeda, "A Japanese-Chinese Cross-Language Entity Linking Method with Entity Disambiguation Based on Document Similarity," International Journal of Knowledge Engineering vol. 2, no. 3, pp. 122-127, 2016.

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