Paper Info
Title
Should we translate the documents or the queries in cross-language information retrieval?
Abstract
Previous comparisons of document and query translation suffered difficulty due to differing quality of machine translation in these two opposite directions. We avoid this difficulty by training identical statistical translation models for both translation directions using the same training data. We investigate information retrieval between English and French, incorporating both translations directions into both document translation and query translation-based information retrieval, as well as into hybrid systems. We find that hybrids of document and query translation-based systems out-perform query translation systems, even human-quality query translation systems.
Year
DOI
Venue
1999
10.3115/1034678.1034716
ACL
Keywords
Field
DocType
cross-language information retrieval,query translation-based system,human-quality query translation system,information retrieval,translation direction,document translation,query translation system,query translation,identical statistical translation model,machine translation,query translation-based information retrieval
Query optimization,Rule-based machine translation,Example-based machine translation,Query language,Query expansion,Information retrieval,Computer science,Machine translation,Artificial intelligence,Natural language processing,Computer-assisted translation,Cross-language information retrieval
Conference
Volume
ISBN
Citations 
P99-1
1-55860-609-3
67
PageRank 
References 
Authors
3.85
14
1
Name
Order
Citations
PageRank
J. Scott Mccarley121421.36