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Digging Deep into the Data Mine with DataMiningGrid

  • Vlado Stankovski
  • , Jernej Trnkoczy
  • , Martin Swain
  • , Werner Dubitzky
  • , Valentin Kravtsov
  • , Assaf Schuster
  • , Thomas Niessen
  • , Dennis Wegener
  • , Michael May
  • , Matthias Röhm
  • , Jürgen Franke

Research output: Contribution to journalArticlepeer-review

Abstract

As modern data mining applications increase in complexity, so too do their demands for resources. Grid computing is one of several emerging networked computing paradigms promising to meet the requirements of heterogeneous, large-scale, and distributed data mining applications. Despite this promise, there are still too many issues to be resolved before grid technology is commonly applied to large-scale data mining tasks. To address some of these issues, the authors developed the DataMiningGrid system. It integrates a diverse set of programs and application scenarios within a single framework, and features scalability, flexible extensibility, sophisticated support for relevant standards and different users.
Original languageEnglish
Pages (from-to)69-76
JournalIEEE Internet Computing
Volume12
Issue number6
Publication statusPublished (in print/issue) - Nov 2008

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