Low-cost, High-performance Translation Retrieval: Dumber is Better 
 In this paper, we compare the relative effects of segment order , segmentation and segment contiguity on the retrieval performance of a translation memory system . We take a selection of both bag-of-words and segment order-sensitive string comparison methods , and run each over both character- and word-segmented data , in combination with a range of local segment contiguity models (in the form of N-grams ). Over two distinct datasets , we find that indexing according to simple character bigrams produces a retrieval accuracy superior to any of the tested word N-gram models . Further,in their optimum configuration , bag-of-words methods are shown to be equivalent to segment order-sensitive methods in terms of retrieval accuracy , but much faster. We also provide evidence that our findings are scalable. 