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

fYear

2008

fDate

12-14 Nov. 2008

Firstpage

334

Lastpage

339

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICEEE.2008.4723406

Filename

4723406