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Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007)
Finding Frequent Items in SlidingWindows over Data Streams Using EBF
Haier International Training Center, Qingdao, China
July 30-August 01
ISBN: 0-7695-2909-7
ASCII Text
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ShuYun Wang, HeXiang Xu, YunFa Hu, "Finding Frequent Items in SlidingWindows over Data Streams Using EBF," Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on, vol. 3, pp. 682-687, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007.
 
 
BibTex
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@article{ 10.1109/SNPD.2007.451,
author = {ShuYun Wang and HeXiang Xu and YunFa Hu},
title = {Finding Frequent Items in SlidingWindows over Data Streams Using EBF},
journal ={Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on},
volume = {3},
year = {2007},
isbn = {0-7695-2909-7},
pages = {682-687},
doi = {http://doi.ieeecomputersociety.org/10.1109/SNPD.2007.451},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
TI - Finding Frequent Items in SlidingWindows over Data Streams Using EBF
SN - 0-7695-2909-7
SP682
EP687
A1 - ShuYun Wang,
A1 - HeXiang Xu,
A1 - YunFa Hu,
PY - 2007
KW - null
VL - 3
JA - Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, ACIS International Conference on
ER -
 
ShuYun Wang, Fudan University, China
HeXiang Xu, Fudan University, China
YunFa Hu, Fudan University, China
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.
Citation:
ShuYun Wang, HeXiang Xu, YunFa Hu, "Finding Frequent Items in SlidingWindows over Data Streams Using EBF," snpd, vol. 3, pp.682-687, Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007), 2007
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