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Article: Collating Texts Using Progressive Multiple Alignment

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Abstract

To reconstruct a stemma or do any other kind of statistical analysis of a text tradition, one needs accurate data on the variants occurring at each location in each witness. These data are usually obtained from computer collation programs. Existing programs either collate every witness against a base text or divide all texts up into segments as long as the longest variant phrase at each point. These methods do not give ideal data for stemma reconstruction. We describe a better collation algorithm (progressive multiple alignment) that collates all witnesses word by word without a base text, adding groups of witnesses one at a time, starting with the most closely related pair.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Dalhousie University, Nova Scotia, Canada

    Matthew Spencer & Christopher Howe

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  1. Matthew Spencer
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  2. Christopher Howe
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Spencer, M., Howe, C. Article: Collating Texts Using Progressive Multiple Alignment. Computers and the Humanities 38, 253–270 (2004). https://doi.org/10.1007/s10579-004-8682-1

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