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Multi-dimensional data analysis and online analytical processing are standard querying techniques applied on today's data warehouses. Data mining algorithms, on the other hand, are mostly run in stand-alone, batch mode on at les extracted from relational databases. In this paper the authors propose a general querying model combining the power of relational databases, SQL, multi-dimensional querying and data mining. Using this model allows data mining to leverage much of the extensive infrastructure that has already been built for data warehouses including many of the highly successful query processing strategies designed for OLAP.
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