Paper: Learning Patterns from the Web to Translate Named Entities for Cross Language Information Retrieval

ACL ID I08-1037
Title Learning Patterns from the Web to Translate Named Entities for Cross Language Information Retrieval
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2008
Authors

Named entity (NE) translation plays an important role in many applications. In this paper, we focus on translating NEs from Korean to Chinese to improve Korean-Chinese cross-language informa- tion retrieval (KCIR). The ideographic nature of Chinese makes NE translation di–cult because one syllable may map to several Chinese characters. We propose a hybrid NE translation system. First, we integrate two online databases to ex- tend the coverage of our bilingual dic- tionaries. We use Wikipedia as a trans- lation tool based on the inter-language links between the Korean edition and the Chinese or English editions. We also use Naver.com’s people search en- gine to flnd a query name’s Chinese or English translation. The second compo- nent is able to learn Korean-Chinese (K- C), Korean-Eng...