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Title: Periodicity Mining in Industrial Data: A Real World Example on Power Data
Author(s): C. Berberidis, I. Vlahavas.
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Appeared in: First International Conference for Mathematics and Informatics for Industry (MII2003), Thessaloniki, 2003.
Abstract: This article presents an approach for detecting weak periodicities in power demand databases. The method attacks the problems in terms of data mining, where the size of the data along with the inherent notion of noise and randomness are crucial factors in the data manipulation process. We target the issue of pe-riodicity, aiming to provide the user with useful time-oriented knowledge about the nature of the data. We conducted experiments over real world power demand data and we exhibit the results.
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