Querying Temporal Drifts at Multiple Granularities - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Preprints, Working Papers, ... Year : 2015

Querying Temporal Drifts at Multiple Granularities


There exists a large body of work on online drift detection 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.
Fichier principal
Vignette du fichier
Querying Temporal Drifts at Multiple Granularities.pdf (2.22 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Dates and versions

hal-01182742 , version 1 (02-09-2015)


Public Domain


  • HAL Id : hal-01182742 , version 1


Sofia Kleisarchaki, Sihem Amer-Yahia, Ahlame Douzal-Chouakria, Vassilis Christophides. Querying Temporal Drifts at Multiple Granularities. 2015. ⟨hal-01182742⟩
567 View
311 Download


Gmail Facebook X LinkedIn More