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.
https://hal.archives-ouvertes.fr/hal-01208397 Contributor : Ahlame DouzalConnect 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