Journal of Information Processing Systems

  • 제13권4호
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  • Pages.716-730
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  • 2017
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Using Semantic Knowledge in the Uyghur-Chinese Person Name Transliteration

  • Murat, Alim (Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Science) ;
  • Osman, Turghun (Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Science) ;
  • Yang, Yating (Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Science) ;
  • Zhou, Xi (Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Science) ;
  • Wang, Lei (Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Science) ;
  • Li, Xiao (Xinjiang Technical Institute of Physics & Chemistry, Chinese Academy of Science)
  • 투고 : 2016.04.21
  • 심사 : 2017.01.31
  • 발행 : 2017.08.31
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초록

In this paper, we propose a transliteration approach based on semantic information (i.e., language origin and gender) which are automatically learnt from the person name, aiming to transliterate the person name of Uyghur into Chinese. The proposed approach integrates semantic scores (i.e., performance on language origin and gender detection) with general transliteration model and generates the semantic knowledge-based model which can produce the best candidate transliteration results. In the experiment, we use the datasets which contain the person names of different language origins: Uyghur and Chinese. The results show that the proposed semantic transliteration model substantially outperforms the general transliteration model and greatly improves the mean reciprocal rank (MRR) performance on two datasets, as well as aids in developing more efficient transliteration for named entities.

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참고문헌

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