Digging Deep into the Data Mine with DataMiningGrid

被引：13

作者：

Stankovski, Vlado ^{[1
]}

Trnkoczy, Jernej ^{[1
]}

Swain, Martin ^{[2
]}

Dubitzky, Werner ^{[2
]}

Kravtsov, Valentin

Schuster, Assaf ^{[3
]}

Niessen, Thomas

Wegener, Dennis

May, Michael

Roehm, Matthias

Franke, Juergen

机构：

[1] Univ Ljubljana, Dept Civil Informat, Fac Civil Geodet Engn, Ljubljana 61000, Slovenia

[2] Univ Ulster, Coleraine BT52 1SA, Londonderry, North Ireland

[3] Technion Israel Inst Technol, Distributed Syst Lab, IL-32000 Haifa, Israel

来源：

IEEE INTERNET COMPUTING | 2008年 / 12卷 / 06期

关键词：

D O I：

10.1109/MIC.2008.122

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

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.

引用

页码：69 / 76

页数：8

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