A novel parallel algorithm for frequent pattern mining with privacy preserved in cloud computing environments

作者：Lin Kawuu W; Deng Der Jiunn^*

来源：International Journal of Ad Hoc and Ubiquitous Computing, 2010, 6(4): 205-215.

• data mining
• cloud computing
• association rule mining
• frequent pattern mining
• privacy preserved
• parallel algorithms
• ubiquitous computing

Parallel and distributed computing techniques have attracted extensive attentions on the ability to manage and compute the significant amount of data in the past decades. The difficulty of mining large database launched the research of designing parallel and distributed algorithms to solve the problem. In this paper, we propose a novel data mining algorithm, named Cloud-based Association Rule Mining (CARM), abbreviated as CARM, which is able to efficiently utilise the nodes to discover frequent patterns in cloud computing environments with data privacy preserved. Through empirical evaluations on various simulation conditions, the proposed CARM delivers excellent performance in terms of scalability and execution time.

• 出版日期2010