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 characterand 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 Ngram models. Further, in their optimum configuration, bag-of-words methods are shown to be equivalent to segment ordersensitive methods in terms of retrieval accuracy, but much faster. We also provide evidence that our findings are scalable.