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Title
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Layers of variation : a computational approach to collating texts with revisions
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Author
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Abstract
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| The article describes research into the automatic comparison of texts with revisions. The authors argue that in-text variation can best be modelled as nonlinear text, and that a collation tool needs to treat in-text variation differently from the way linear text is treated. They describe in detail how the modelling choices they made influence the development of HyperCollate, a collation software that is able to process TEI-XML transcriptions of texts with variation. Consequently, HyperCollate produces a more refined collation output that corresponds with a human interpretation of textual variance.The article describes research into the automatic comparison of texts with revisions. The authors argue that in-text variation can best be modelled as nonlinear text, and that a collation tool needs to treat in-text variation differently from the way linear text is treated. They describe in detail how the modelling choices they made influence the development of HyperCollate, a collation software that is able to process TEI-XML transcriptions of texts with variation. Consequently, HyperCollate produces a more refined collation output that corresponds with a human interpretation of textual variance. |
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Language
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English
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Source (journal)
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DHQ : digital humanities quarterly. - -
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Publication
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2022
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ISSN
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1938-4122
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Volume/pages
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16
:1
(2022)
, p. 1-29
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ISI
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000999080500001
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Medium
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E-only publicatie
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Full text (open access)
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