Combining Induction Methods with the Multimethod Approach

View Sample PDF

Author(s): Mitja Lenic (University of Maribor, FERI, Slovenia), Peter Kokol (University of Maribor, FERI, Slovenia), Petra Povalej (University of Maribor, FERI, Slovenia)and Milan Zorman (University of Maribor, FERI, Slovenia)
Copyright: 2005
Pages: 6
Source title: Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch036

Keywords: Data Mining and Databases / Data Warehousing / Information Science Reference / Library & Information Science

Purchase

View Combining Induction Methods with the Multimethod Approach on the publisher's website for pricing and purchasing information.

Abstract

The aggressive rate of growth of disk storage and, thus, the ability to store enormous quantities of data have far outpaced our ability to process and utilize that. This challenge has produced a phenomenon called data tombs—data is deposited to merely rest in peace, never to be accessed again. But the growing appreciation that data tombs represent missed opportunities in cases supporting scientific discovering, business exploitation, or complex decision making has awakened the growing commercial interest in knowledge discovery and data-mining techniques. That, in order, has stimulated new interest in the automatic knowledge induction from cases stored in large databases—a very important class of techniques in the data-mining field. With the variety of environments, it is almost impossible to develop a single-induction method that would fit all possible requirements. Thereafter, we constructed a new so-called multi-method approach, trying out some original solutions.

The IRMA Community

Research IRM

Combining Induction Methods with the Multimethod Approach

Purchase

Abstract

Related Content

IRMA Sponsors