DocumentCode
2028742
Title
Mining global frequent subtrees
Author
Zhao, Chuanshen ; Jia, Baoxian ; Liu, Yuhua ; Chen, Lixia
Author_Institution
Sch. of Comput. Sci., Liaocheng Univ., Liaocheng, China
Volume
5
fYear
2010
fDate
10-12 Aug. 2010
Firstpage
2275
Lastpage
2279
Abstract
Discovering global frequent subtrees from ordered labeled trees in distribute environment is an attractive research problem in data mining. In this paper, a new algorithm FAMDFS (Fast Algorithm for Mining Global Frequent Subtree) was proposed. This algorithm transfer local projected branch frequent nodes, can decrease network traffic, improve the efficiency of the algorithm. Theoretical analysis and experimental results show that FAMDFS algorithm is efficient and effective.
Keywords
data mining; tree data structures; FAMDFS algorithm; data mining; global frequent subtree mining; local projected branch frequent nodes; network traffic; ordered labeled trees; Algorithm design and analysis; Association rules; Generators; Itemsets; Silicon; global frequent subtree; induced subtree; projected branch; tree mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-5931-5
Type
conf
DOI
10.1109/FSKD.2010.5569315
Filename
5569315
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