This paper proposes an example driven approach to improve the quality of MT system outputs.
we extend the system combination method in SMT to combine the examples by two strategies: 1) estimating the confidence of examples by the similarity between source input and the source part of examples; 2) approximating target word posterior probability by the word alignments of the bilingual examples.