A maximum entropy approach to natural language processing
Computational Linguistics
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Applying Machine Translation to Two-Stage Cross-Language Information
AMTA '00 Proceedings of the 4th Conference of the Association for Machine Translation in the Americas on Envisioning Machine Translation in the Information Future
Matching meaning for cross-language information retrieval
Information Processing and Management: an International Journal
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We describe a statistical algorithm for machine translation intended to provide translations of large document collections at speeds far in excess of traditional machine translation systems, and of sufficiently high quality to perform information retrieval on the translated document collections. The model is trained from a parallel corpus and is capable of disambiguating senses of words. Information retrieval (IR) experiments on a French language dataset from a recent cross-language information retrieval evaluation yields results superior to those obtained by participants in the evaluation, and confirm the importance of word sense disambiugation in cross-language information retrieval.