Paper Info
Title
The maintenance of representative frequent itemsets
Abstract
Mining frequent itemsets is to discover the groups of items appearing always together excess of a user specified threshold from a transaction database. However, there may be many frequent itemsets existing in a transaction database, such that it is difficult to make a decision for a decision maker. Recently, mining frequent closed itemsets becomes a major research issue, since all frequent itemsets can be derived from frequent closed itemsets. In addition, the transactions in a database will be increased and removed constantly. It is a challenge that how to update the previous frequent closed itemsets from the increased and removed transactions. In our previous researches, we have proposed an algorithm MRFI to maintain the frequent closed itemsets when the transactions are added into a transaction database. In this paper, we propose an efficient algorithm for maintaining frequent closed itemsets when the transactions are deleted from a transaction database without scanning original database. Our algorithm updates closed itemsets by some rules without taking a lot of time to search the previous closed itemsets. The experimental results show that our algorithm significantly outperforms the previous approaches which need to take a lot of time to search the previous closed itemsets.
Year
DOI
Venue
2010
10.1109/ICMLC.2010.5580928
ICMLC
Keywords
Field
DocType
database management systems,frequent itemsets,frequent closed itemsets mining,data stream,data mining,closed itemsets,transaction database,cybernetics,machine learning,algorithm design and analysis,decision maker
Data mining,Algorithm design,Data stream,Computer science,Database transaction,Cybernetics,Decision maker,Decision-making
Conference
Volume
ISBN
Citations 
5
978-1-4244-6526-2
0
PageRank 
References 
Authors
0.34
7
3
Name
Order
Citations
PageRank
Show-Jane Yen1537130.05
Yue-Shi Lee254341.14
Chiu-Kuang Wang3293.10