DocumentCode :
3423309
Title :
A fast parallel algorithm for discovering frequent patterns
Author :
Lin, Kawuu W. ; Luo, Yu-Chin
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Kaohsiung Univ. of Appl. Sci., Kaohsiung, Taiwan
fYear :
2009
fDate :
17-19 Aug. 2009
Firstpage :
398
Lastpage :
403
Abstract :
Fast discovery of frequent patterns is the most extensively discussed problem in data mining fields due to its wide applications. As the size of database increases, the computation time and the required memory increase severely. The difficulty of mining large database launched the research of designing parallel and distributed algorithms to solve the problem. Most of the past studies tried to parallelize the computation by dividing the database and distribute the divided database to other nodes for mining. This approach might leak data out and evidently is not suitable to be applied to sensitive domains like health-care. In this paper, we propose a novel data mining algorithm named FD-Mine that is able to efficiently utilize the nodes to discover frequent patterns in cloud computing environments with data privacy preserved. Through empirical evaluations on various simulation conditions, the proposed FD-Mine delivers excellent performance in terms of scalability and execution time.
Keywords :
data mining; data privacy; parallel algorithms; association rule mining; data mining algorithm; data privacy; database mining; distributed algorithm; fast parallel algorithm; frequent pattern discovery; Algorithm design and analysis; Cloud computing; Computational modeling; Concurrent computing; Data mining; Data privacy; Distributed algorithms; Distributed computing; Distributed databases; Parallel algorithms; Data mining; association rule mining; cloud computing; frequent pattern mining; privacy preserved;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location :
Nanchang
Print_ISBN :
978-1-4244-4830-2
Type :
conf
DOI :
10.1109/GRC.2009.5255089
Filename :
5255089
Link To Document :
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