The term Online Analytical Mining, coined in 1997 by J. Han [9], refers to solutions that integrate online analytical processing (OLAP) with data mining functionalities so that mining can be performed in different portions of databases or data warehouses and at different levels of abstraction at the user’s fingertips. In such a system, data mining techniques will beneficiate of a higher level of integration, consistency, and cleanness, and data warehouse users will be able to express more powerful queries directly from their user interface. Although no commercial tools make available a complete and integrated set of OLAM features, many data mining techniques have been extended to deal with specific data warehouse features, while new algorithms, that specifically address the OLAP user’s advanced requirements, have been developed.
Golfarelli, M. (2016). OLAM. New York : Springer [10.1007/978-1-4899-7993-3_80662-1].
OLAM
GOLFARELLI, MATTEO
2016
Abstract
The term Online Analytical Mining, coined in 1997 by J. Han [9], refers to solutions that integrate online analytical processing (OLAP) with data mining functionalities so that mining can be performed in different portions of databases or data warehouses and at different levels of abstraction at the user’s fingertips. In such a system, data mining techniques will beneficiate of a higher level of integration, consistency, and cleanness, and data warehouse users will be able to express more powerful queries directly from their user interface. Although no commercial tools make available a complete and integrated set of OLAM features, many data mining techniques have been extended to deal with specific data warehouse features, while new algorithms, that specifically address the OLAP user’s advanced requirements, have been developed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
