• DocumentCode
    3356709
  • Title

    Click2Annotate: Automated Insight Externalization with rich semantics

  • Author

    Chen, Yang ; Barlowe, Scott ; Yang, Jing

  • Author_Institution
    Dept. of Comput. Sci., UNC Charlotte, Charlotte, NC, USA
  • fYear
    2010
  • fDate
    25-26 Oct. 2010
  • Firstpage
    155
  • Lastpage
    162
  • Abstract
    Insight Externalization (IE) refers to the process of capturing and recording the semantics of insights in decision making and problem solving. To reduce human effort, Automated Insight Externalization (AIE) is desired. Most existing IE approaches achieve automation by capturing events (e.g., clicks and key presses) or actions (e.g., panning and zooming). In this paper, we propose a novel AIE approach named Click2Annotate. It allows semi-automatic insight annotation that captures low-level analytics task results (e.g., clusters and outliers), which have higher semantic richness and abstraction levels than actions and events. Click2Annotate has two significant benefits. First, it reduces human effort required in IE and generates annotations easy to understand. Second, the rich semantic information encoded in the annotations enables various insight management activities, such as insight browsing and insight retrieval. We present a formal user study that proved this first benefit. We also illustrate the second benefit by presenting the novel insight management activities we developed based on Click2Annotate, namely scented insight browsing and faceted insight search.
  • Keywords
    data mining; data visualisation; decision making; information retrieval; problem solving; user interfaces; Click2Annotate; decision making; insight browsing; insight externalization; insight management activity; insight retrieval; problem solving; Automation; Book reviews; Compounds; Context; Mice; Prototypes; Semantics; Annotation; Decision Making; Insight Management; Multidimensional Visualization; Visual Analytics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology (VAST), 2010 IEEE Symposium on
  • Conference_Location
    Salt Lake City, UT
  • Print_ISBN
    978-1-4244-9488-0
  • Electronic_ISBN
    978-1-4244-9487-3
  • Type

    conf

  • DOI
    10.1109/VAST.2010.5652885
  • Filename
    5652885