Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
PRES: a score metric for evaluating recall-oriented information retrieval applications
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Looking inside the box: context-sensitive translation for cross-language information retrieval
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
Flat vs. hierarchical phrase-based translation models for cross-language information retrieval
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
| Hi-index | 0.00 |
The translation stage in cross language information retrieval (CLIR) acts as the main enabling stage to cross the language barrier between documents and queries. In recent years machine translation (MT) systems have become the dominant approach to translation in CLIR. However, unlike information retrieval (IR), MT focuses on the morphological and syntactical quality of the sentence. This requires large training resources and high computational power for training and translation. We present a novel technique for MT designed specifically for CLIR. In this method IR text pre-processing in the form of stop word removal and stemming are applied to the MT training corpus prior to the training phase. Applying this pre-processing step is found to significantly speed up the translation process without affecting the retrieval quality.