Cross-lingual information retrieval by feature vectors

  • Authors:
  • Jeanine Lilleng;Stein L. Tomassen

  • Affiliations:
  • Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway

  • Venue:
  • NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper investigates query translation in cross-lingual information retrieval, especially the challenges caused by ambiguity and polysemi. We base our ideas on feature vectors and our method uses context during the translation of queries. Achieving good query translation can be difficult, due to short queries lacking context information. We argue that by using information external to the query, like ontologies and document collections, the effect of ambiguity and polysemi can be reduced. Different approaches for translation of these feature vectors are proposed and discussed.