Statistical Machine Translation and Cross-Language IR: QMUL at CLEF 2006

In this year’s CLEF submissions we focus on using a state-of-the-art statistical machine translation approach for ad-hoc cross-language retrieval. Our machine translation approach is phrase-based as opposed to statistical word-based approaches that have been previously used for query translation in cross-language IR. The phrase translation probabilities were estimated by using the Europarl corpus. For query formulation, we also use the n-best lists of translation candidates to assign weights to query terms. Our results show that a statistical phrase-based approach is a competitive alternative to commercial, rule-based machine translation approaches in the context of cross-language IR.