Inductive databases are intended to be general purpose databases in which both source data and mined patterns can be represented, retrieved and manipulated. However, the heterogeneity of models for mined patterns makes difficult to realize them. In this paper, we explore the feasibility of using XML as the unifying framework for inductive databases, introducing a suitable data model called XDM (XML for data mining). XDM is designed to describe source raw data, heterogeneous mined patterns and data mining statements, so that they can be stored inside a unique XML-based inductive database.

Toward XML-Based Knowledge Discovery Systems

MEO, Rosa;
2002

Abstract

Inductive databases are intended to be general purpose databases in which both source data and mined patterns can be represented, retrieved and manipulated. However, the heterogeneity of models for mined patterns makes difficult to realize them. In this paper, we explore the feasibility of using XML as the unifying framework for inductive databases, introducing a suitable data model called XDM (XML for data mining). XDM is designed to describe source raw data, heterogeneous mined patterns and data mining statements, so that they can be stored inside a unique XML-based inductive database.
Second IEEE International Conference on Data Mining
Maebashi City, Japan
DECEMBER 2002
Proceedings of the Second IEEE International Conference on Data Mining
IEEE Computer Society
-
665
668
9780769517544
Meo, Rosa; Psaila, G.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/18594
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