Improving Translation of Organization Names Combining Translation Model and Web Mining

Named entity (NE) translation is a fundamental task in machine translation (MT) and cross-language information retrieval (CLIR). Furthermore, Organization name (ON) translation is the most complex among all the NEs. A novel system for translating ONs from Chinese to English, with a translation model and web resources, is proposed. Firstly, we built a translation model with Chunk. Then query expansion was adopted with the translation model and term-subject co-occurrence. Thirdly, we extracted the Chinese Organization names with English sentences using the method of frequency shifting and adjacency information to find English fragments as translation candidates. Finally, we found the best translation by computing the trustworthiness of all candidates. The experimental results showed that the approach returned a better performance than machine translation-based systems.

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