DataJewel: Integrating Visualization with Temporal Data Mining

  • Mihael Ankerst
  • Anne Kao
  • Rodney Tjoelker
  • Changzhou Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4404)


In this chapter we describe DataJewel, a new temporal data mining architecture. DataJewel tightly integrates a visualization component, an algorithmic component and a database component. We introduce a new visualization technique called CalendarView as an implementation of the visualization component, and we introduce a data structure that supports temporal mining of large databases. In our architecture, algorithms can be tightly integrated with the visualization component and most existing temporal data mining algorithms can be leveraged by embedding them into DataJewel. This integration is achieved by an interface that is used by both the user and the algorithms to assign colors to events. The user interactively assigns colors to incorporate domain knowledge or to formulate hypotheses. The algorithm assigns colors based on discovered patterns. The same visualization technique is used for displaying both data and patterns to make it more intuitive for the user to identify useful patterns while exploring data interactively or while using algorithms to search for patterns. Our experiments in analyzing several large datasets from the airplane maintenance domain demonstrate the usefulness of our approach and we discuss its applicability to domains like homeland security, market basket analysis and web mining.


Event Type Intrusion Detection Visualization Technique Color Assignment Event Attribute 
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 2008

Authors and Affiliations

  • Mihael Ankerst
    • 1
  • Anne Kao
    • 2
  • Rodney Tjoelker
    • 2
  • Changzhou Wang
    • 2
  1. 1.  MünchenGermany
  2. 2.The Boeing CompanySeattle

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