Article ID Journal Published Year Pages File Type
385541 Expert Systems with Applications 2011 13 Pages PDF
Abstract

A data warehouse is an important decision support system with cleaned and integrated data for knowledge discovery and data mining systems. In reality, the data warehouse mining system has provided many applicable solutions in industries, yet there are still many problems causing users extra problems in discovering knowledge or even failing to obtain the real and useful knowledge they need. To improve the overall data warehouse mining process, we present an intelligent data warehouse mining approach incorporated with schema ontology, schema constraint ontology, domain ontology and user preference ontology. The structures of these ontologies are illustrated and how they benefit the mining process is also demonstrated by examples utilizing rule mining. Finally, we present a prototype multidimensional association mining system, which with intelligent assistance through the support of the ontologies, can help users build useful data mining models, prevent ineffective pattern generation, discover concept extended rules, and provide an active knowledge re-discovering mechanism.

► Contemporary warehouse systems lack assistance in crystallizing user mining intention. ► This paper proposes an ontology-based intelligent data warehouse mining system. ► Four ontologies are built to facilitate intelligent setting of a user’s mining model. ► Benefits of the proposed system are illustrated by multidimensional association mining. ► A prototype system with intelligent assistance through the ontologies is demonstrated.

Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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