ARMADA - An algorithm for discovering richer relative temporal association rules from interval-based data

@article{Winarko2007ARMADAA,
  title={ARMADA - An algorithm for discovering richer relative temporal association rules from interval-based data},
  author={Edi Winarko and John F. Roddick},
  journal={Data Knowl. Eng.},
  year={2007},
  volume={63},
  pages={76-90}
}
Temporal association rule mining promises the ability to discover time-dependent correlations or patterns between events in large volumes of data. To date, most temporal data mining research has focused on events existing at a point in time rather than over a temporal interval. In comparison to static rules, mining with respect to time points provides semantically richer rules. However, accommodating temporal intervals offers rules that are richer still. In this paper we outline a new algorithm… CONTINUE READING
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