Incremental mining of frequent patterns without candidate generation or support constraint

Author

Cheung, William ; Zaïane, Osmar R.

Author_Institution

Alberta Univ., Edmonton, Alta., Canada

fYear

2003

Firstpage

111

Lastpage

116

Abstract

In this paper, we propose a novel data structure called CATS Tree. CATS Tree extends the idea of FPTree to improve storage compression and allow frequent pattern mining without generation of candidate item sets. The proposed algorithms enable frequent pattern mining with different supports without rebuilding the tree structure. Furthermore, the algorithms allow mining with a single pass over the database as well as efficient insertion or deletion of transactions at any time.

Keywords

data compression; data mining; pattern recognition; storage management; transaction processing; tree data structures; CATS Tree; Compressed and Arranged Transaction Sequences tree; FPTree; association rule mining; candidate generation; candidate item set; data compression; data structure; frequent pattern; incremental mining; iterative process; memory footprint reduction; memory management; single pass mining; storage compression improvement; support constraint; transaction deletion; transaction insertion; tree structure rebuilding; Association rules; Cats; Costs; Data compression; Data mining; Itemsets; Iterative algorithms; Memory management; Transaction databases; Tree data structures;

fLanguage

English

Publisher

ieee

Conference_Titel

Database Engineering and Applications Symposium, 2003. Proceedings. Seventh International

ISSN

1098-8068

Print_ISBN

0-7695-1981-4

Type

conf

DOI

10.1109/IDEAS.2003.1214917

Filename

1214917