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