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Visualization for the Masses: Learning from the Experts

  • Jill Freyne
  • Barry Smyth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6176)

Abstract

Increasingly, in our everyday lives, we rely on our ability to access and understand complex information. Just as the search engine played a key role in helping people access relevant information, there is evidence that the next generation of information tools will provide users with a greater ability to analyse and make sense of large amounts of raw data. Visualization technologies are set to play an important role in this regard. However, the current generation of visualization tools are simply too complex for the typical user. In this paper we describe a novel application of case-based reasoning techniques to help users visualize complex datasets. We exploit an online visualization service, ManyEyes, and explore how case-based representation of datasets including simple features such as size and content types can produce recommendations to assist novice users in the selection of appropriate visualization types.

Keywords

Novice User Case Representation Recommendation List Recommendation Strategy Target Case 
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 2010

Authors and Affiliations

  • Jill Freyne
    • 1
  • Barry Smyth
    • 2
  1. 1.Tasmanian ICT Center, CSIROTasmaniaAustralia
  2. 2.CLARITY: Centre for Sensor Web Technologies, School of Computer Science and InformaticsUniversity College DublinDublinIreland

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