Learning to Translate: A Query-Specific Combination Approach for Cross-Lingual Information Retrieval

When documents and queries are pre-sented in different languages, the com-mon approach is to translate the query into the document language. While there are a variety of query translation approaches, recent research suggests that combining multiple methods into a single ”structured query ” is the most effective. In this pa-per, we introduce a novel approach for producing a unique combination recipe for each query, as it has also been shown that the optimal combination weights dif-fer substantially across queries and other task specifics. Our query-specific combi-nation method generates statistically sig-nificant improvements over other combi-nation strategies presented in the litera-ture, such as uniform and task-specific weighting. An in-depth empirical anal-ysis presents insights about the effect of data size, domain differences, labeling and tuning on the end performance of our ap-proach. 1