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Mining Translations of Chinese Names from Web Corpora Using a Query Expansion Technique and Support Vector Machine

机译:使用查询扩展技术和支持向量机从Web Cotora挖掘中文名称的挖掘翻译

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Chinese name translation is a special case of the problem of named entity translation. It is a very challenging problem because there exist many kinds of Romanization systems and some people like to add additional words into their English names. Translating a scholar's name to its corresponding English name could help find information about his academic achievements. In this paper, we provide a classification for Chinese names, and propose a novel approach to mining Chinese name translations from Web corpora. Our approach is based on three kinds of features, namely the phonetic similarity, the smallest distance, and the number of appearances in the neighborhood, to extract name translation candidates by using a query expansion technique and Support Vector Machine (SVM). Experimental results show that our approach can correctly translate the majority of Chinese names.
机译:中文名称翻译是命名实体翻译问题的特殊情况。这是一个非常具有挑战性的问题,因为存在许多罗马化系统,有些人喜欢将额外的单词添加到他们的英文名称中。将学者的名字翻译成其相应的英文名称可以帮助找到有关他的学术成就的信息。在本文中,我们为中文名称提供了分类,并提出了一种新的挖掘Web Corpora汉语翻译的方法。我们的方法是基于三种特征,即语音相似性,最小的距离和邻域的出现数量,通过使用查询扩展技术来提取名称翻译候选,并支持向量机(SVM)。实验结果表明,我们的方法可以正确翻译大多数中文名称。

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