Combination Methods for Improving the Reliability of Machine Translation Based Cross-Language Information Retrieval
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Cross-Language Information Retrieval (CLIR) is an important topic in the increasingly multilingual environment of online information. Experiments usingthe standard CLEF 2001 bilingual task show that Machine Translation (MT) can provide effective search topic translation for CLIR, and that retrieval performance can be improved and made more reliable by applyinga combination of pseudo-relevance feed-back, corpus methods and data merging.
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