Incremental updating algorithm for infrequent itemsets on weighted condition

Author

Dong, Wenjuan ; Jiang, He ; Chen, Lei ; Liu, Guoling

Author_Institution

Sch. of Inf. Sci. & Technol., Shandong Inst. of Light Ind., Jinan, China

Volume

1

fYear

2010

fDate

25-27 June 2010

Abstract

Association rules are dedicated to describe the direct correlations among the items in frequent itemsets, while negative association rules are dedicated to describe the indirect correlations between the two items in infrequent itemsets. Incremental updating algorithm is important for mining infrequent itemset in dynamic databases. A new algorithm for mining infrequent itemsets from weighted incremental updating database (MIIWIU), is proposed to deal with the incremental updating problem when anew database is inserted in the original database and the minimum support is not changed to mine frequent and infrequent itemsets. The experiment results have shown that our approach is efficient and promising.

Keywords

data mining; database management systems; association rules; dynamic databases; incremental updating algorithm; infrequent itemset mining; weighted condition; Algorithm design and analysis; Association rules; Computer industry; Data mining; Helium; Information science; Investments; Itemsets; Pattern recognition; Transaction databases; Incremental Updating; Infrequent Itemset; Weight;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Design and Applications (ICCDA), 2010 International Conference on

Conference_Location

Qinhuangdao

Print_ISBN

978-1-4244-7164-5

Electronic_ISBN

978-1-4244-7164-5

Type

conf

DOI

10.1109/ICCDA.2010.5541039

Filename

5541039