DocumentCode
2179013
Title
A Survey of Algorithms in FCIM
Author
Shekofteh, Maryam
Author_Institution
Sarvestan Branch, Islamic Azad Univ., Shiraz, Iran
fYear
2010
fDate
9-10 Feb. 2010
Firstpage
29
Lastpage
33
Abstract
Frequent closed itemsets (FCI) is a condensed representation method for frequent item-sets. FCI reduces the redundant rules and increases the performance of mining. In recent years, a large number of algorithms have been proposed about frequent closed itemsets mining due to the importance of them In this paper, we generally review and compare the most important FCI algorithms with each other. Results show that each algorithm based on its applied strategy has some advantages and disadvantages for mining in dense and sparse datasets. However, DCI-Closed algorithm is more effective than other ones.
Keywords
data mining; condensed representation method; data mining; frequent closed itemsets mining; redundant rules; Association rules; Classification algorithms; Costs; Data engineering; Data mining; Itemsets; Lattices; Memory; Production; Transaction databases; Association rule mining; frequent closed itemset;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Storage and Data Engineering (DSDE), 2010 International Conference on
Conference_Location
Bangalore
Print_ISBN
978-1-4244-5678-9
Type
conf
DOI
10.1109/DSDE.2010.32
Filename
5452619
Link To Document