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Term distribution visualizations with Focus+Context

Overview and usability evaluation

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Abstract

Many text searches are meant to identify one particular fact or one particular section of a document. Unfortunately, predominant search paradigms focus mostly on identifying relevant documents and leave the burden of within-document searching on the user. This research explores term distribution visualizations as a means to more clearly identify both the relevance of documents and the location of specific information within them. We present a set of term distribution visualizations, introduce a Focus+Context model for within-document search and navigation, and describe the design and results of a 34-subject user study. This user study shows that these visualizations—with the exception of the grey scale histogram variant—are comparable in usability to our Grep interface. This is impressive given the substantial experience of our users with Grep functionality. Overall, we conclude that user do not find this visualization model difficult to use and understand.

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Acknowledgements

This work was supported in part by NSF Grant #0313885 and Sandia National Laboratories. Statistical analysis of user study data was performed primarily with R [16].

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Authors and Affiliations

  1. Department of Computer Science and Engineering, New Mexico Institute of Mining and Technology, Socorro, NM, USA

    Moses Schwartz, Curtis Hash & Lorie M. Liebrock

  2. Sandia National Laboratories, Albuquerque, NM, USA

    Moses Schwartz

Authors
  1. Moses Schwartz
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  2. Curtis Hash
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  3. Lorie M. Liebrock
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Corresponding author

Correspondence to Moses Schwartz.

Additional information

This work was supported in part by NSF Grant #0313885 and Sandia National Laboratories.

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Schwartz, M., Hash, C. & Liebrock, L.M. Term distribution visualizations with Focus+Context. Multimed Tools Appl 50, 509–532 (2010). https://doi.org/10.1007/s11042-010-0479-1

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