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

Kawuu W. Lin, Der Jiunn Deng

研究成果: Article

36 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)205-215
頁數11
期刊International Journal of Ad Hoc and Ubiquitous Computing
6
發行號4
DOIs
出版狀態Published - 2010 一月 1

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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