DocumentCode
3405332
Title
An Algorithm for Mining Frequent Items on Data Stream Using Fading Factor
Author
Chen, Ling ; Zhang, Shan ; Tu, Li
Author_Institution
Dept. of Comput. Sci., Yangzhou Univ., Yangzhou, China
Volume
2
fYear
2009
fDate
20-24 July 2009
Firstpage
172
Lastpage
177
Abstract
An algorithm using a fading factor to detect the frequent data items in a stream is presented. Our algorithm can detect epsiv-approximate frequent data items on data stream using O(L+epsiv-1) memory space where L is a constant, and the processing time for each data item is O(1). Experimental results on several artificial datasets and real datasets show our algorithm has higher precision, requires less memory and computation time than other similar methods.
Keywords
data mining; artificial dataset; data mining frequent item; data stream; fading factor; real dataset; Application software; Computer applications; Computer science; Counting circuits; Data mining; Fading; Frequency; Information science; Sampling methods; Software algorithms; data mining; data stream; frequent items; time fading model;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Software and Applications Conference, 2009. COMPSAC '09. 33rd Annual IEEE International
Conference_Location
Seattle, WA
ISSN
0730-3157
Print_ISBN
978-0-7695-3726-9
Type
conf
DOI
10.1109/COMPSAC.2009.130
Filename
5254129
Link To Document