关键词: 汉语, 泰语, 双语人名对齐, 人名知识分布, 分类结果调优

Abstract: The study of bilingual name alignment method directly affects the effect of cross-language information processing. For the pronunciation of Chinese is quite different from Thai, and the resources of Chinese-Thai bilingual corpus are limited, and the present transliteration bilingual name alignment model based on statistics is not enough to solve those problems, this paper proposes a method which based on transliteration features, merges the similarity of the name knowledge distribution characteristics. Firstly, it calculates the similarity characteristics of bilingual name transliteration. Then the similarity of knowledge distribution characteristics between Chinese and Thai names is calculated by Chi-square test and others. Support vector machine is used to learn two features of translation of Chinese-Thai personal names to generate personal names translation pair classifier，the alignment results are generated by optimizing the classifier classification results. Experimental results show that this method has also achieved better results, even if bilateral people’s pronunciation is quite difference and lacking of bilingual corpus resources.

Key words: Chinese, Thai, bilingual name alignment, name knowledge distribution, adjusting and optimizing classification results