Journal of Data Mining and Digital Humanities (Mar 2018)
Identification of Parallel Passages Across a Large Hebrew/Aramaic Corpus
Abstract
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 Babylonian Talmud, a Hebrew-Aramaic corpus of over 1.8 million words, in just over 30 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. Comment: Submission to the Journal of Data Mining and Digital Humanities (Special Issue on Computer-Aided Processing of Intertextuality in Ancient Languages)
