Given a collection of imperfect copies of a textual document, the aim of stemmatology is to reconstruct the history of the text, indicating for each variant the sourcc tcxt from it was copied. We describe an experiment involving three artificial bcnchmark data sets to which a number of computer-assisted stemmatologr mcthods wcre applied. Contrary to earlicr similar expcrimenls, we propose and use a numerical criterion to evaluate all the solutions. Moreover, our primary data set is significantly !arger than used before. The results suggest the superiorit}' of two computer-assisted methods amongst those tested: the maximum parsimony method implemented in the PAUP• software package and a related compression-based method we have proposed in earlier work.
One related research area where the problem is also the identification of which text is the copy and which text is the source is computational stemmatology "Given a collection of imperfect copies of a textual document, the aim of stemmatology is to reconstruct the history of the text, indicating for each variant the source text from it was copied." REF The methods used there are phylogenetic methods borrowed from evolutionary biology.
Evaluating methods for computer-assisted stemmatology using artificial benchmark data sets
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Computer Science