Title :
Mining global frequent subtrees
Author :
Zhao, Chuanshen ; Jia, Baoxian ; Liu, Yuhua ; Chen, Lixia
Author_Institution :
Sch. of Comput. Sci., Liaocheng Univ., Liaocheng, China
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569315
