Statistical Machine Translation based Passage Retrieval for Cross-Lingual Question Answering.
Tomoyosi Akiba, Kei Shimizu, Atsushi Fujii · 2008
In this paper, we propose a novel approach for Cross-Lingual Question Answering (CLQA). In the proposed method, the statistical machine translation (SMT) is deeply incorporated into the question answering process, instead of using it as the pre-processing of the mono-lingual QA process as in the previous work. The proposed method can be considered as exploiting the SMT-based passage retrieval for CLQA task. We applied our method to the English-to-Japanese CLQA system and evaluated the performance by using NTCIR CLQA 1 and 2 test collections. The result showed that the proposed method outperformed the previous pre-translation approach. 1