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The Effectiveness of Results Re-Ranking and Query Expansion in Cross-language Information Retrieval

paper presents the technique details and experimental results of the information retrieval system with which we participated at the NTCIR-8 ACLIA (Advanced Cross-language Information Access) IR4QA (Information Retrieval for Question Answering) task. Document corpus in Simplified Chinese (CS) and Traditional Chinese (CT) with topics in English, CS and CT were used in our experiments. We combined the query expansion and initial retrieval results re-ranking techniques as main retrieval approach. The experimental results confirmed that query expansion based on Bose-Einstein distribution and re-ranking method based on Latent Dirichlet Allocation (LDA) are able to consistently bring significant improvements over various baseline systems. Especially the approach is capable of processing mixed- multilingual text obtained by a machine translator for cross- language information retrieval (CLIR). The results obtained might provide us more insight and understanding into cross-language query expansion and document re-ranking.