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Translating-Transliterating Named Entities for Multilingual Information Access

, , , and . Journal of the American Society for Information Science and Technology, (2006)

Abstract

Named entities are major constituents of a document but are usually unknown words. This work proposes a systematic way of dealing with formulation, transformation, translation, and transliteration of multilingual-named entities. The rules and similarity matrices for translation and transliteration are learned automatically from parallel-named-entity corpora. The results are applied in cross-language access to collections of images with captions. Experimental results demonstrate that the similarity-based transliteration of named entities is effective, and runs in which transliteration is considered outperform the runs in which it is neglected.

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