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Communicative Signals as the Key to Automated Understanding of Simple Bar Charts

  • Stephanie Elzer
  • Sandra Carberry
  • Seniz Demir
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4045)

Abstract

This paper discusses the types of communicative signals that frequently appear in simple bar charts and how we exploit them as evidence in our system for inferring the intended message of an information graphic. Through a series of examples, we demonstrate the impact that various types of communicative signals, namely salience, captions and estimated perceptual task effort, have on the intended message inferred by our implemented system.

Keywords

Bayesian Network Perceptual Task Communicative Signal Information Graphic Graphic Designer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Stephanie Elzer
    • 1
  • Sandra Carberry
    • 2
  • Seniz Demir
    • 2
  1. 1.Dept of Computer ScienceMillersville Univ.MillersvilleUSA
  2. 2.Dept of Computer ScienceUniv. of DelawareNewarkUSA

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