Title :
An Algorithm for Mining Frequent Itemsets
Author :
Leon, R.H. ; Suarez, A.P. ; Uribe, C.F. ; Zavaleta, Z.J.G.
Author_Institution :
Adv. Technol. Applic. Center, CENATAV, Cuba
Abstract :
In this paper, we propose a new algorithm for mining frequent itemsets. This algorithm is named AMFI (Algorithm for Mining Frequent Itemsets). This algorithm compresses the data while maintaining the necessary semantics for the frequent itemsets mining problem and it is more efficient that traditional compression algorithms. The AMFI efficiency is based on a compressed vertical binary representation of the data and on a very fast support count. AMFI performs a breadth first search through equivalence classes. We compare our proposal with an implementation using PackBits algorithm.
Keywords :
data compression; data mining; data structures; equivalence classes; set theory; tree searching; binary data representation; breadth first search; data compression; equivalence classes; frequent itemset mining algorithm; Astrophysics; Automatic control; Compression algorithms; Dairy products; Data mining; Electronic mail; Itemsets; Iterative algorithms; Optical computing; Proposals; compression algorithms; data mining; frequent patterns;
Conference_Titel :
Electrical Engineering, Computing Science and Automatic Control, 2008. CCE 2008. 5th International Conference on
Conference_Location :
Mexico City
Print_ISBN :
978-1-4244-2498-6
Electronic_ISBN :
978-1-4244-2499-3
DOI :
10.1109/ICEEE.2008.4723406
