DocumentCode :
3164980
Title :
Research on association rules mining algorithm with item constraints
Author :
Lu, Nan ; Wang-Zhe ; Zhou, Chun-Guang ; Zhou, Jing-Zhou
Author_Institution :
Coll. of Inf. Eng., Shenzhen Univ.
fYear :
2005
fDate :
23-25 Nov. 2005
Lastpage :
329
Abstract :
The issues in the field of association rules mining with specific items are discussed first. To solve the problems in the ordinary algorithm, we put forward a new but efficient mining algorithm with item-constraints, called EclatII. We then give an analysis on the performance of the algorithm as well as on its strategy. The experimental result shows that the Eclatll algorithm is more robust in items of using "low support\´"\´ and "long pattern" association rules than others
Keywords :
data mining; EclatII algorithm; association rules mining; frequent item set; item constraints; lattice theory; performance analysis; Algorithm design and analysis; Association rules; Computer science; Constraint theory; Data mining; Educational institutions; Frequency; Lattices; Partitioning algorithms; Transaction databases; association rules; data mining; frequent item-set; item constrains; lattice theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyberworlds, 2005. International Conference on
Conference_Location :
Singapore
Print_ISBN :
0-7695-2378-1
Type :
conf
DOI :
10.1109/CW.2005.77
Filename :
1587551
Link To Document :
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