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 introduced in a previous paper. 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.

A Tightly-Coupled Architecture for Data Mining

MEO, Rosa;
1998

Abstract

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 introduced in a previous paper. 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.
IEEE International Conference on Data Engineering
ORLANDO, FLORIDA, USA
FEBRUARY
Proceedings of the Fourteenth International Conference on Data Engineering
IEEE Computer Society
14
316
323
9780818682896
http://www.informatik.uni-trier.de/~ley/db/conf/icde/icde98.html
Meo, Rosa; Psaila, G.; Ceri, S.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/18592
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