While this strategy was shown to be superior to random as well as n-gram based dissimilarity selection, its coarse granularity (reducing a candidate sentence to a lowdimensional feature vector for ranking) makes it unsuitable for many situations.
it is seen to have little or no benefit over random selection when there is no logical separation of the candidate pool into "in-domain" and "out-of-domain" subsets.