Visualizing Uncertainty in Lattices to Support Decision-Making. Collins, C., Carpendale, S., & Penn, G. In Proceedings of the Eurographics/IEEE VGTC Symposium on Visualization, Norrköping, Sweden, May, 2007. http://diglib.eg.org
abstract   bibtex   
Lattice graphs are used as underlying data structures in many statistical processing systems, including natural language processing. Lattices compactly represent multiple possible outputs and are usually hidden from users. We present a novel visualization intended to reveal the uncertainty and variability inherent in statistically-derived lattice structures. Applications such as machine translation and automated speech recognition typically present users with a best-guess about the appropriate output, with apparent complete confidence. Through case studies we show how our visualization uses a hybrid layout along with varying transparency, colour, and size to reveal the lattice structure, expose the inherent uncertainty in statistical processing, and help users make better-informed decisions about statistically-derived outputs.
@InProceedings{	  collins1,
  author	= {Christopher Collins and Sheelagh Carpendale and Gerald
		  Penn},
  title		= {Visualizing Uncertainty in Lattices to Support
		  Decision-Making},
  booktitle	= {{Proceedings of the Eurographics/IEEE VGTC Symposium on
		  Visualization}},
  address	= {Norrköping, Sweden},
  month		= {May},
  year		= {2007},
  abstract	= {Lattice graphs are used as underlying data structures in
		  many statistical processing systems, including natural
		  language processing. Lattices compactly represent multiple
		  possible outputs and are usually hidden from users. We
		  present a novel visualization intended to reveal the
		  uncertainty and variability inherent in
		  statistically-derived lattice structures. Applications such
		  as machine translation and automated speech recognition
		  typically present users with a best-guess about the
		  appropriate output, with apparent complete confidence.
		  Through case studies we show how our visualization uses a
		  hybrid layout along with varying transparency, colour, and
		  size to reveal the lattice structure, expose the inherent
		  uncertainty in statistical processing, and help users make
		  better-informed decisions about statistically-derived
		  outputs.},
  note		= {http://diglib.eg.org}
}

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