An Algorithm for Mining Frequent Stream Data Items Using Hash Function and Fading Factor

Abstract:

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A new algorithm to mine the frequent items in data stream is presented. The algorithm adopts a time fading factor to emphasize the importance of the relatively newer data, and records the densities of the data items in Hash tables. For a given threshold of density S and an integer k, our algorithm can mine the top k frequent items. Computation time for processing each data item is O(1) . Experimental results show that the algorithm outperforms other methods in terms of accuracy, memory requirement, and processing speed.

Info:

Periodical:

Edited by:

Han Zhao

Pages:

2661-2665

DOI:

10.4028/www.scientific.net/AMM.130-134.2661

Citation:

Q. L. Mei and L. Chen, "An Algorithm for Mining Frequent Stream Data Items Using Hash Function and Fading Factor", Applied Mechanics and Materials, Vols. 130-134, pp. 2661-2665, 2012

Online since:

October 2011

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Price:

$35.00

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