Abstract
OLAP mining is a mechanism which integrates on-line analytical processing (OLAP) with data mining so that mining can be performed in different portions of databases or data warehouses and at different levels of abstraction at user’s finger tips. With rapid developments of data warehouse and OLAP technologies in database industry, it is promising to develop OLAP mining mechanisms.
With our years of research into data mining, an OLAP-based data mining system, DBMiner, has been developed, where OLAP mining is not only for data characterization but also for other data mining functions, including association, classification, prediction, clustering, and sequencing. Such an integration increases the flexibility of mining and helps users find desired knowledge. In this paper, we introduce the concept of OLAP mining and discuss how OLAP mining should be implemented in a data mining system.
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© 1998 Springer Science+Business Media Dordrecht
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Han, J. (1998). OLAP Mining: An Integration of OLAP with Data Mining. In: Spaccapietra, S., Maryanski, F. (eds) Data Mining and Reverse Engineering. IFIP — The International Federation for Information Processing. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35300-5_1
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DOI: https://doi.org/10.1007/978-0-387-35300-5_1
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