Finding Frequent Items in SlidingWindows over Data Streams Using EBF

Authors:
ShuYun Wang;HeXiang Xu;YunFa Hu
Affiliations:
Fudan University, China;Fudan University, China;Fudan University, China
Venue:
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03
Year:
2007

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Data Mining and Knowledge Discovery

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Abstract

This paper introduces the algorithm FIS-EBF for estimating the frequent items in sliding windows over data streams. FIS-EBF is Based the data structure named EBF(extensible Bloom Filter). Experiments show that FISEBF can work with high precision and recall, it is also showed that FIS-EBF is very efficient in terms of processing time.