@InProceedings{ryskina-EtAl:2017:Short,
  author    = {Ryskina, Maria  and  Alpert-Abrams, Hannah  and  Garrette, Dan  and  Berg-Kirkpatrick, Taylor},
  title     = {Automatic Compositor Attribution in the First Folio of Shakespeare},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {411--416},
  abstract  = {Compositor attribution, the clustering of pages in a historical printed
	document by the individual who set the type, is a bibliographic task that
	relies on analysis of orthographic variation and inspection of visual details
	of the printed page. In this paper, we introduce a novel unsupervised model
	that jointly describes the textual and visual features needed to distinguish
	compositors. Applied to images of Shakespeare's First Folio, our model predicts
	attributions that agree with the manual judgements of bibliographers with an
	accuracy of 87%, even on text that is the output of OCR.},
  url       = {http://aclweb.org/anthology/P17-2065}
}