Querying Temporal Drifts at Multiple Granularities

Sofia Kleisarchaki, Sihem Amer-Yahia, Ahlame Douzal-Chouakria, Vassilis Christophides
2015 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management - CIKM '15  
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 querybased 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 materializations of the
more » ... alizations 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.
doi:10.1145/2806416.2806436 dblp:conf/cikm/KleisarchakiACC15 fatcat:5oovtg5cpnfwzghsbk36figmfi