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 journalArticle

    24 Citations (Scopus)

    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 - Nov 2008

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  • Cite this

    Stankovski, V., Trnkoczy, J., Swain, M., Dubitzky, W., Kravtsov, V., Schuster, A., Niessen, T., Wegener, D., May, M., Röhm, M., & Franke, J. (2008). Digging Deep into the Data Mine with DataMiningGrid. IEEE Internet Computing, 12(6), 69-76.