DocumentCode :
604508
Title :
Design and implementation of improved algorithm for frequent item sets mining
Author :
Zhang Lin ; Zhang Jianli
Author_Institution :
Dept. of Comput. Sci. & Technol., AnHui SanLian Univ., Hefei, China
fYear :
2012
fDate :
29-31 Dec. 2012
Firstpage :
1696
Lastpage :
1698
Abstract :
A new frequent item sets mining algorithm based on linked list and stack data structure at the Apriori algorithm´s expensive disadvantage is given in this paper. This method create frequent item sets based on the linked list series and use the stack structure and subset judgment method to judge if the created frequent item sets are the maximum frequent item sets. Through demonstrates we can see that this method is cheap, with high accuracy and can provide some reference for related rules.
Keywords :
data mining; data structures; Apriori algorithm; frequent item sets mining algorithm; linked list series; stack data structure; subset judgment method; algorithm; data mining; frequent item sets; implementarion; linked list;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
Type :
conf
DOI :
10.1109/ICCSNT.2012.6526247
Filename :
6526247
Link To Document :
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