Service-oriented distributed data mining

Kwok Wai CHEUNG*, Xiao Feng Zhang, Ho Fai Wong, Jiming LIU, Zong Wei Luo, Frank C.H. Tong

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

Data mining research currently faces two great challenges: how to embrace data mining services with just-in-time and autonomous properties and how to mine distributed and privacy-protected data. To address these problems, the authors adopt the Business Process Execution Language for Web Services in a serviceoriented distributed data mining (DDM) platform to choreograph DDM component services and fulfill global data mining requirements. They also use the learning-from-abstraction methodology to achieve privacy-preserving DDM. Finally,they illustrate how localized autonomy on privacy-policy enforcement plus a bidding process can help the service-oriented system self-organize.

Original languageEnglish
Pages (from-to)44-54
Number of pages11
JournalIEEE Internet Computing
Volume10
Issue number4
DOIs
Publication statusPublished - Jul 2006

Scopus Subject Areas

  • Computer Networks and Communications

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