DocumentCode :
483227
Title :
An Association Rule Algorithm Based on Quotient Space
Author :
Zhang, Yueqin ; Yan, Qingwei ; Zong, Lili
Author_Institution :
Coll. of Comput. & Software, Taiyuan Univ. of Technol., Taiyuan
fYear :
2009
fDate :
23-25 Jan. 2009
Firstpage :
223
Lastpage :
226
Abstract :
Finding the large item set fast is the crucial step in the association rule algorithm. In this paper we apply granular computing and quotient space to frequent item set discovering , by partition the information system to information granule and mapping granule object sets, the algorithm reduced the number of database scanning and reduced object sets required when computing support of candidate item, in this way we improved the efficient of running. For the dataset of small support with high complexity, it is more applicable. The experiment results show: the proposed method is effective.
Keywords :
data mining; database management systems; association rule; database scanning; frequent item set discovering; granular computing; information system; quotient space; Association rules; Data mining; Data structures; Databases; Educational institutions; Information systems; Itemsets; Partitioning algorithms; Software algorithms; Space technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3543-2
Type :
conf
DOI :
10.1109/WKDD.2009.133
Filename :
4771918
Link To Document :
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