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A study on designing a Layered Star Schema for data mining optimization

机译:设计分层星形模式进行数据挖掘优化的研究

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摘要

Granularity refers to the level of detail of the data stored fact tables in a data warehouse. All the tools and techniques for Data mining mainly concerned with availability of huge storage of data in Data warehouse. Required relevant information can be derived only after searching and accessing related data items from the Data Warehouse which requires a query cost investment and some time it may return very minimal or even zero valued result. Therefore our proposed Layered Star Schema can help the Data miners to optimize their Data mining model with appropriate dimension before triggering their Data mining application to Data Warehouse.
机译:粒度是指数据仓库中存储的事实表数据的详细程度。数据挖掘的所有工具和技术主要涉及数据仓库中海量数据的可用性。仅在从数据仓库中搜索和访问相关数据项之后才可以获取所需的相关信息,这需要进行查询成本投资,并且有时可能会返回非常少的值甚至为零值。因此,我们提出的分层星型架构可以帮助数据挖掘者在触发其数据挖掘应用程序到数据仓库之前,以适当的维度优化其数据挖掘模型。

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