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A tightly-coupled architecture for data mining

机译:用于数据挖掘的紧密耦合架构

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Current approaches to data mining are based on the use of a decoupled architecture, where data are first extracted from a database and then processed by a specialized data mining engine. This paper proposes instead a tightly-coupled architecture, where data mining is integrated within a classical SQL server. The premise of this work is a SQL-like operator, called MINE RULE. We show how the various syntactic features of the operator can be managed by either a SQL engine or a classical data mining engine; our main objective is to identify the border between typical relational processing, executed by the relational server, and data mining processing, executed by a specialized component. The resulting architecture exhibits portability at the SQL level and integration of inputs and outputs of the data mining operator with the database, and provides the guidelines for promoting the integration of other data mining techniques and systems with SQL servers.
机译:数据挖掘的电流方法基于使用解耦架构,其中首先从数据库中提取数据,然后由专用数据挖掘引擎处理。本文提出了紧密耦合的架构,其中数据挖掘集成在经典的SQL Server中。这项工作的前提是SQL类似的操作员,称为Mine Rule。我们展示了如何通过SQL引擎或经典数据挖掘引擎管理的操作员的各种句法特征;我们的主要目标是识别由关联服务器和数据挖掘处理执行的典型关系处理之间的边界,由专用组件执行。生成的架构在SQL级别和数据挖掘运算符的输入和输出与数据库的集成以及与SQL服务器的集成的指南提供了指南。

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