Notes on Experiments with Pseudo Relevance Feedback and Data Merging In Cross-Language Retrieval

In the TREC-8 cross-language information retrieval (CLIR) track, we adopted the approach of using machine translation to prepare a source-language query for use in a target-language retrieval task. We empirically evaluated (1) the effect of pseudo relevance feedback on retrieval performance with two feedback vector length control methods in CLIR, and (2) the effect of multilingual data merging either before or after retrieval. Our experiments show that, in general, pseudo relevance feedback significantly improves cross-language retrieval performance, and that post-retrieval merging of retrieval results can outperform pre-retrieval merging of multilingual data collections.