Artikel in Tagungsband INPROC-2007-29

Monteiro, Rodrigo; Zimbrao, Geraldo; Schwarz, Holger; Mitschang, Bernhard; Souza, Jano: DWFIST: Leveraging Calendar-based Pattern Mining in Data Streams.
In: Proc. of the 9th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2007) Regensburg, Germany, 3-7 September, 2007.
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 438-448, englisch.
-, September 2007.
Artikel in Tagungsband (Konferenz-Beitrag).
CR-Klassif.H.2.8 (Database Applications)

Calendar-based pattern mining aims at identifying patterns on specific calendar partitions. Potential calendar partitions are for example: every Monday, every first working day of each month, every holiday. Providing flexible mining capabilities for calendar-based partitions is especially challenging in a data stream scenario. The calendar partitions of interest are not known a priori and at each point in time only a subset of the detailed data is available. We show how a data warehouse approach can be applied to this problem. The data warehouse that keeps track of frequent itemsets holding on different partitions of the original stream has low storage requirements. Nevertheless, it allows to derive sets of patterns that are complete and precise. This work demonstrates the effectiveness of our approach by a series of experiments.

Abteilung(en)Universität Stuttgart, Institut für Parallele und Verteilte Systeme, Anwendersoftware
Eingabedatum20. Juli 2007
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