In this experiment, average precision on training data proves to be the best predictor of additional relevant documents: ∼71% of the test questions benefit from queries based on average precision feature selection.
recently (riezler et al., 2007) used statistical machine translation for query expansion and took a step towards bridging the lexical gap between questions and answers.