On the bursty evolution of blogspace
WWW '03 Proceedings of the 12th international conference on World Wide Web
Bursty and Hierarchical Structure in Streams
Data Mining and Knowledge Discovery
Efficient elastic burst detection in data streams
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Reducing unwanted traffic in a backbone network
SRUTI'05 Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop
Mining correlated bursty topic patterns from coordinated text streams
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Online Burst Detection Over High Speed Short Text Streams
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Detecting Click Fraud in Pay-Per-Click Streams of Online Advertising Networks
ICDCS '08 Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems
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A burst, i.e., an unusally high frequency of an event in a time-window, is interesting in monitoring systems as it often indicates abnormality. While the detection of bursts is well addressed, the question of what "critical" thresholds, on the number of events as well as on the window size, make a window "unusally bursty" remains a relevant one. The range of possible values for either threshold can be very large. We formulate finding the combination of critical thresholds as a 2D search problem and design efficient deterministic and randomized divide-and-conquer heuristics. For both, we show that under some weak assumptions, the computational overhead in the worst case is logarithmic in the sizes of the ranges. Our simulations show that on average, the randomized heuristic beats its deteministic counterpart in practice.