Cross-lingual information retrieval using hidden Markov models

  • Authors:
  • Jinxi Xu;Ralph Weischedel

  • Affiliations:
  • BBN Technologies, Cambridge, MA;BBN Technologies, Cambridge, MA

  • Venue:
  • EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
  • Year:
  • 2000

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents empirical results in cross-lingual information retrieval using English queries to access Chinese documents (TREC-5 and TREC-6) and Spanish documents (TREC-4). Since our interest is in languages where resources may be minimal, we use an integrated probabilistic model that requires only a bilingual dictionary as a resource. We explore how a combined probability model of term translation and retrieval can reduce the effect of translation ambiguity. In addition, we estimate an upper bound on performance, if translation ambiguity were a solved problem. We also measure performance as a function of bilingual dictionary size.