DocumentCode :
1941325
Title :
FP-Growth Algorithm for Application in Research of Market Basket Analysis
Author :
Liu, Yongmei ; Guan, Yong
Author_Institution :
Capital Normal Univ., Beijing
fYear :
2008
fDate :
27-29 Nov. 2008
Firstpage :
269
Lastpage :
272
Abstract :
During the process of mining frequent item sets, when minimum support is little, the production of candidate sets is a kind of time-consuming and frequent operation in the mining algorithm. The FP growth algorithm does not need to produce the candidate sets, the database which provides the frequent item set is compressed to a frequent pattern tree (or FP tree), and frequent item set is mining by using of FP tree. For the sake of researching market basket analysis, the frequent-pattern is introduced, Visual C++ is applied to design the program to mine the frequent item sets. In view of the frequent K-item set, the various results are contrasted, the goods which is sell possibly at the same time in the supermarket is arranged in the same place.
Keywords :
business data processing; data mining; FP growth algorithm; Visual C++; frequent K-item set; market basket analysis; mining algorithm; Algorithm design and analysis; Association rules; Business; Costs; Data mining; Marketing and sales; Organizational aspects; Partitioning algorithms; Production; Visual databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Cybernetics, 2008. ICCC 2008. IEEE International Conference on
Conference_Location :
Stara Lesna
Print_ISBN :
978-1-4244-2874-8
Electronic_ISBN :
978-1-4244-2875-5
Type :
conf
DOI :
10.1109/ICCCYB.2008.4721419
Filename :
4721419
Link To Document :
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