DocumentCode :
479012
Title :
ARCA: An Algorithm for Mining Association Rules Based Concept Lattice
Author :
Xia, Qing ; Wang, Sujing ; Chen, Zhen ; Lv, Tao ; Wang, Dongjing
Author_Institution :
Huaihai Inst. of Technol., Lianyungang
fYear :
2008
fDate :
12-14 Oct. 2008
Firstpage :
1
Lastpage :
5
Abstract :
Association rule discovery is one of kernel tasks of data mining. Concept lattice, induced from a binary relation between objects and features, is a very useful formal analysis tool. It represents the unification of concept intension and extension. It reflects the association between objects and features, and the relationship of generalization and specialization among concepts. There is a one-to-one correspondence between concept intensions and closed frequent itemsets. This paper presents an efficient algorithm for mining association rules based concept lattice called Area (Association Rule based Concept lAttice). Area algorithm uses concept-matrix to build a part of concept lattice, in which the intension of every concept be put into one-to-one correspondence with a closed frequent itemset. Then all association rules are discovered by 4 operators which are defined in this paper performed on these concepts.
Keywords :
data mining; matrix algebra; ARCA; association rule based concept lattice; concept-matrix; data mining; formal analysis tool; Association rules; Computer science; Data mining; Educational institutions; Itemsets; Kernel; Lattices; Libraries; Transaction databases; Weapons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-2107-7
Electronic_ISBN :
978-1-4244-2108-4
Type :
conf
DOI :
10.1109/WiCom.2008.2586
Filename :
4680775
Link To Document :
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