Translating-transliterating named entities for multilingual information access
Journal
Journal of the American Society for Information Science and Technology
Journal Volume
57
Journal Issue
5
Pages
645-659
Date Issued
2006
Author(s)
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. © 2006 Wiley Periodicals, Inc.
SDGs
Type
journal article