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Integrating Local and Global Data View for Bilingual Sense Correspondences

  • Fumiyo FukumotoEmail author
  • Yoshimi Suzuki
  • Attaporn Wangpoonsarp
  • Meng Ji
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 976)

Abstract

This paper presents a method of linking and creating bilingual sense correspondences between English and Japanese noun word dictionaries. We used local and global data views to identify bilingual sense correspondences. Locally, we extracted bilingual noun words by using simple sentence-based similarity. Globally, for each monolingual dictionary, we estimated domain-specific senses by using a textual corpus having category information. The extraction method is based on the sense similarities which are obtained by word embedding learning. We incorporated these data views. More precisely, we assigned a sense to each noun word of the extracted bilingual words keeping domain (category) consistency. We used the WordNet 3.0 and EDR Japanese dictionaries using Reuters and Mainichi Japanese newspaper corpora to evaluate our method. The results showed that the integration of local and global data views improved overall performance and we obtained 318 within the topmost 1,000 bilingual noun senses. Moreover, we found that the extracted bilingual noun senses can be used as a lexical resource for the machine translation as the translation results obtained by using our method was better than those obtained by a bilingual dictionary and slightly better than the results obtained by SYSTRANet.

Keywords

Bilingual sense correspondence Domain specific senses Word embeddings 

Notes

Acknowledgements

The authors would like to thank Bernardo Magnini for providing SFC resources, and the anonymous reviewers for their comments and suggestions. This work was supported by the Telecommunications Advancement Foundation, and Support Center for Advanced Telecommunications Technology Research, Foundation.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Fumiyo Fukumoto
    • 1
    Email author
  • Yoshimi Suzuki
    • 1
  • Attaporn Wangpoonsarp
    • 1
  • Meng Ji
    • 2
  1. 1.Graduate Faculty of Interdisciplinary ResearchUniversity of YamanashiKofuJapan
  2. 2.University of SydneySydneyAustralia

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