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