Abstract
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 feedback, corpus methods and data merging.
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Jones, G.J.F., Lam-Adesina, A.M. (2002). Combination Methods for Improving the Reliability of Machine Translation Based Cross-Language Information Retrieval. In: O’Neill, M., Sutcliffe, R.F.E., Ryan, C., Eaton, M., Griffith, N.J.L. (eds) Artificial Intelligence and Cognitive Science. AICS 2002. Lecture Notes in Computer Science(), vol 2464. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45750-X_25
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DOI: https://doi.org/10.1007/3-540-45750-X_25
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