Abstract In the last decade the dominant models of MT have been data-driven or corpus-based. Of the two main trends, statistical machine translation and example-based machine translation (EBMT), the latter is much less clearly defined. In a review of the recently published collection edited by Michael Carl and Andy Way, this essay surveys the basic processes, methods, main problems and tasks of EBMT, and attempts to provide a definition of the essence of EBMT in comparison with statistical MT and traditional rule-based MT.
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