DocumentCode :
2742341
Title :
A New Method for Incremental Updating Frequent Patterns Mining
Author :
He, Hai-tao ; Zhang, Shi-Ling
Author_Institution :
YanShan Univ., Qinhuangdao
fYear :
2007
fDate :
5-7 Sept. 2007
Firstpage :
561
Lastpage :
561
Abstract :
Frequent patterns mining has been studied popularly in KDD research. However, little work has been done on incremental updating frequent patterns mining. In a real transaction database, as time changing many new data may be inserted into previous database. But it is hard to handle incremental updating problems with FP-growth algorithm. In this paper, a novel incremental updating pattern tree (INUP_Tree) structure is presented, which is constructed by scanning database only once. And a new frequent pattern mining method (IUF_Mine) based on conditional matrix is developed. When database is updated, only the new added records will be scanned. Besides, original conditional matrix can be adequately used to speed up the new mining process, so the mining efficiency is improved. The experiment result shows that the IUF_Mine method is more efficient and faster than the FP-growth.
Keywords :
data mining; database management systems; matrix algebra; tree data structures; conditional matrix; incremental updating frequent patterns mining; incremental updating pattern tree structure; transaction database; Association rules; Data engineering; Data mining; Data structures; Educational institutions; Helium; Information science; Transaction databases; Tree data structures;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control, 2007. ICICIC '07. Second International Conference on
Conference_Location :
Kumamoto
Print_ISBN :
0-7695-2882-1
Type :
conf
DOI :
10.1109/ICICIC.2007.51
Filename :
4428203
Link To Document :
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