Translating Unknown Words by Analogical Learning

Unknown words are a well-known hindrance to natural language applications. In particular, they drastically impact machine translation quality. An easy way out commercial translation systems usually offer their users is the possibility to add unknown words and their translations into a dedicated lexicon. Recently, Stroppa and Yvon (2005) have shown how analogical learning alone deals nicely with morphology in different languages. In this study we show that analogical learning offers as well an elegant and effective solution to the problem of identifying potential translations of unknown words.

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