Corpora of manuscripts of the same ancient text often preserve many variants. This is so because upon copying over long copy chains errors and editorial changes have been repeatedly made and reverted to the effect that most often no 2 variant texts of the same so-called textual tradition have exactly the same text. Obviously in order to save the time to read all of the versions and in order to enable discourse and unambiguous referencing, philologists have since the beginnings of the age of print embarked on providing one single textual representation of this variety. In computational terms one tries to retrieve/compose the base text which is most likely the latest common ancestor (archetype) of all observed variants. Computationally, stemmata – that is trees depicting the copy history (manuscripts = nodes, Copy processes = edges) – have been computed and evaluated automatically (Roos and Heikkilä, 2009). Likewise, automatic archetype reconstruction has been introduced lately, (Hoenen, 2015b; Koppel et al., 2016). A synthesis of both stemma generation and archetype reconstruction has not yet been achieved. This paper therefore presents an approach where through iterative clustering a stemma and an archetype text are being reconstructed bottom-up.
@InProceedings{HOENEN18.314, author = {Armin Hoenen}, title = "{From Manuscripts to Archetypes through Iterative Clustering}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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