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This article describes a framework for cross-language information retrieval that efficiently leverages statistical estimation of translation probabilities. The framework provides a unified perspective into which some earlier work on techniques for cross-language information retrieval based on translation probabilities can be cast. Modeling synonymy and filtering translation probabilities using bidirectional evidence are shown to yield a balance between retrieval effectiveness and query-time (ordoi:10.1016/j.ipm.2011.09.003 fatcat:rsoxmr67jrb3tmifyqgtk6kpwe