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Querying Temporal Drifts at Multiple Granularities

Abstract : There exists a large body of work on online drift detec- tion with the goal of dynamically finding and maintaining changes in data streams. In this paper, we adopt a query- based approach to drift detection. Our approach relies on a drift index, a structure that captures drift at different time granularities and enables flexible drift queries. We formalize different drift queries that represent real-world scenarios and develop query evaluation algorithms that use different mate- rializations of the drift index as well as strategies for online index maintenance. We describe a thorough study of the performance of our algorithms on real-world and synthetic datasets with varying change rates.
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Contributor : Ahlame Douzal Connect in order to contact the contributor
Submitted on : Friday, October 2, 2015 - 3:18:43 PM
Last modification on : Sunday, June 26, 2022 - 5:00:58 AM


  • HAL Id : hal-01208397, version 1



Sofia Kleisarchaki, Sihem Amer-yahia, Ahlame Douzal-Chouakria, Vassilis Christophides. Querying Temporal Drifts at Multiple Granularities. CIKM 2015, Oct 2015, Melbourne, Australia. ⟨hal-01208397⟩



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