JIPS (한국정보처리학회)
Current Result Document :
| 한글제목(Korean Title) |
Using Semantic Knowledge in the Uyghur-Chinese Person Name Transliteration |
| 영문제목(English Title) |
Using Semantic Knowledge in the Uyghur-Chinese Person Name Transliteration |
| 저자(Author) |
Alim Murat
Turghun Osman
Yating Yang
Xi Zhou
Lei Wang
Xiao Li
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| 원문수록처(Citation) |
VOL 13 NO. 04 PP. 0716 ~ 0730 (2017. 08) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
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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| 키워드(Keyword) |
Gender
Language Origin
Semantic Knowledge-based Model
Transliteration of Person Name
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| 파일첨부 |
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