DocumentCode
523673
Title
A New Method for Eliminating Redundant Association Rules
Author
Xin, Ye ; Na, Wang ; Chunyu, Wang
Author_Institution
Inst. of Inf. & Decision Technol., Dalian Univ. of Technol., Dalian, China
Volume
1
fYear
2010
fDate
11-12 May 2010
Firstpage
32
Lastpage
36
Abstract
As one of the fundamental data mining methods, the association rule mining has widely been used in many fields. However, the existence of massive redundant rules has made the analysis very difficult, and has been a main barrier to efficient utilization of discovered association rules. This paper studies the characteristic of commonsense knowledge which is use to eliminate redundant association rules, and analyzes the impact of commonsense knowledge and the special rules whose confidence is 100% on the generation of redundant rules. Some theorems and corollaries of redundant rules are proposed and a new method for eliminating redundant rules based on these theories is proposed. This new method can prune some redundant rules by using commonsense knowledge and the special rules without calculating confidence, so it improved the efficiency of mining and the utilization of discovered association rules.
Keywords
Association rules; Automation; Character generation; Customer relationship management; Data analysis; Data mining; Intrusion detection; Itemsets; Road accidents; Security; Association Rule Mining; Commonsense Knowledge; Redundant Rules;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location
Changsha, China
Print_ISBN
978-1-4244-7279-6
Electronic_ISBN
978-1-4244-7280-2
Type
conf
DOI
10.1109/ICICTA.2010.129
Filename
5522795
Link To Document