Research of Improved FP-Growth Algorithm in Association Rules Mining
Joint Authors
Zeng, Yi
Yin, Shiqun
Liu, Jiangyue
Zhang, Miao
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-15
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Association rules mining is an important technology in data mining.
FP-Growth(frequent-pattern growth) algorithm is a classical algorithm in association rules mining.
But the FP-Growth algorithm in mining needs two times to scan database, which reduces the efficiency of algorithm.
Through the study of association rules mining and FP-Growth algorithm, we worked out improvedalgorithms of FP-Growth algorithm—Painting-Growth algorithm and N (not) Painting-Growth algorithm(removes the painting steps, and uses another way to achieve).
We compared two kinds of improved algorithmswith FP-Growth algorithm.
Experimental results show that Painting-Growth algorithm is more than 1050 and NPainting-Growth algorithm is less than 10000 in data volume; the performance of the two kinds of improvedalgorithms is better than that of FP-Growth algorithm.
American Psychological Association (APA)
Zeng, Yi& Yin, Shiqun& Liu, Jiangyue& Zhang, Miao. 2015. Research of Improved FP-Growth Algorithm in Association Rules Mining. Scientific Programming،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1076557
Modern Language Association (MLA)
Zeng, Yi…[et al.]. Research of Improved FP-Growth Algorithm in Association Rules Mining. Scientific Programming No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1076557
American Medical Association (AMA)
Zeng, Yi& Yin, Shiqun& Liu, Jiangyue& Zhang, Miao. Research of Improved FP-Growth Algorithm in Association Rules Mining. Scientific Programming. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1076557
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1076557