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Distributed and parallel data mining on the grid

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dc.contributor.authorLi, Tianchao
dc.contributor.authorBollinger, Toni
dc.contributor.editorBrinkschulte, Uwe
dc.contributor.editorBecker, Jürgen
dc.contributor.editorFey, Dietmar
dc.contributor.editorGroßpietsch, Karl-Erwin
dc.contributor.editorHochberger, Christian
dc.contributor.editorMaehle, Erik
dc.contributor.editorRunkler, Thomas A.
dc.date.accessioned2019-10-30T11:53:45Z
dc.date.available2019-10-30T11:53:45Z
dc.date.issued2004
dc.description.abstractThis paper presents the initial design and implementation of a Gridbased distributed and parallel data mining system. The Grid system, namely the Business Intelligence Grid or BIGrid, is based on heterogeneous Grid server configurations and service-oriented Grid architecture. The system follows a layered design, whose infrastructure is divided into three tiers in general - Grid tier, a service tier and a client/portal tier. Issues of design and implementation, including brokering, task scheduling, adaptive mining script preparation and parallelization are discussed. The design and implementation of BIGrid help identify the specific requirements of applying Grid-based data mining in business realm, thus pave way for future design and implementation of a real generic Gridbased data mining system.en
dc.identifier.isbn3-88579-370-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/29390
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofARCS 2004 – Organic and pervasive computing
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-41
dc.titleDistributed and parallel data mining on the griden
dc.typeText/Conference Paper
gi.citation.endPage379
gi.citation.publisherPlaceBonn
gi.citation.startPage370
gi.conference.dateMarch 26, 2004
gi.conference.locationAugsburg
gi.conference.sessiontitleRegular Research Papers

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P041 - ARCS 2004 - Organic and Pervasive Computing