Paper Info
Title
Efficient Algorithms for Mining Closed Itemsets and Their Lattice Structure
Abstract
The set of frequent closed itemsets uniquely determines the exact frequency of all itemsets, yet it can be orders of magnitude smaller than the set of all frequent itemsets. In this paper, we present CHARM, an efficient algorithm for mining all frequent closed itemsets. It enumerates closed sets using a dual itemset-tidset search tree, using an efficient hybrid search that skips many levels. It also uses a technique called diffsets to reduce the memory footprint of intermediate computations. Finally, it uses a fast hash-based approach to remove any "nonclosed驴 sets found during computation. We also present CHARM-L, an algorithm that outputs the closed itemset lattice, which is very useful for rule generation and visualization. An extensive experimental evaluation on a number of real and synthetic databases shows that CHARM is a state-of-the-art algorithm that outperforms previous methods. Further, CHARM-L explicitly generates the frequent closed itemset lattice.
Year
DOI
Venue
2005
10.1109/TKDE.2005.60
IEEE Trans. Knowl. Data Eng.
Keywords
Field
DocType
index terms—closed itemsets,efficient hybrid search,frequent closed itemsets,state-of-the-art algorithm,association rules,mining closed itemsets,closed itemset lattice,efficient algorithm,data mining.,lattice structure,exact frequency,frequent itemsets,frequent closed itemset lattice,present charm-l,dual itemset-tidset search tree,efficient algorithms,search tree,lattices,association rule,indexing terms,data visualization,multidimensional systems,data mining,degradation,frequency
Data mining,Data visualization,Computer science,Algorithm,Closed set,Association rule learning,Hash function,Memory footprint,Search tree,Multidimensional systems,Computation
Journal
Volume
Issue
ISSN
17
4
1041-4347
Citations 
PageRank 
References 
324
10.75
21
Authors
2
Search Limit
100324
Name
Order
Citations
PageRank
Mohammed Javeed Zaki17972536.24
Ching-Jui Hsiao233913.17