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DataJewel: Tightly integrating visualization with temporal data mining

By Mihael Ankerst, David H. Jones, Anne Kao and Changzhou Wang


Abstract. In this paper we describe DataJewel, a new architecture designed for temporal data mining. It 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. We show how algorithms can be tightly integrated with the visualization component and that most existing temporal data mining algorithms can be leveraged by embedding them into our architecture. This integration is achieved by an interface that is used by the user and the algorithm to assign colors to events. The user assigns colors to interactively incorporate domain knowledge or to formulate hypotheses. The algorithm assigns colors based on the discovered patterns. Using the same visualization technique for both data and patterns makes it more intuitive for the user to select useful patterns from those returned by the algorithm. We also present a data structure that supports temporal mining of very large databases. In the experiments, we apply our approach to several large datasets from the airplane maintenance domain and discuss its applicability to domains like homeland security, market basket analysis and web mining.

Year: 2003
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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