Translating–transliterating named entities for multilingual information access

  • Authors:

  • Hsin-Hsi Chen;Wen-Cheng Lin;Changhua Yang;Wei-Hao Lin

  • Affiliations:

  • Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan;Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan;Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

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.