We propose a method for efficiently finding all parallel passages in a large corpus, even if the passages are not quite identical due to rephrasing and orthographic variation. The key ideas are the representation of each word in the corpus by its two most infrequent letters, finding matched pairs of strings of four or five words that differ by at most one word and then identifying clusters of such matched pairs. Using this method, over 4600 parallel pairs of passages were identified in the

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... onian Talmud, a Hebrew-Aramaic corpus of over 1.8 million words, in just over 11 seconds. Empirical comparisons on sample data indicate that the coverage obtained by our method is essentially the same as that obtained using slow exhaustive methods. keywords approximate matching; fuzzy matching; text reuse INTRODUCTION Ancient text corpora in classical languages such as Greek, Latin, Hebrew and Aramaic typically include numerous examples of text reuse, including repetitions of long passages of 20 words or more. Identifying such passages is important because it allows scholars to trace the development of ideas and concepts through time and across geographical ranges. Additionally, even within a given time period and geographical location, the identification of multiple parallel sources for any given idea provides a platform for scholarly inquiry. Identifying all examples of text reuse within a large such corpus is challenging for several reasons, including the large number of comparisons that must be done and the fact that matches tend to be only approximate.