Héctor Oscar Nigro (INCA/INTIA, Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina) and Sandra Elizabeth González Císaro (Universidad Nacional del Centro de la Provincia de Buenos Aires, Argentina)
Copyright: © 2005
Knowledge discovery is defined as “the non trivial extraction of implicit, unknown, and potentially useful knowledge of the data” (Fayyad, Piatetsky-Shiapiro, Smyth, & Uthurusamy, 1996, p. 6). According to these principles, the knowledge discovery process (KDP) takes the results just as they come from the data (i.e., the process of extracting tendencies or models of the data), and it carefully and accurately transforms them into useful and understandable information. To consider the discovery of knowledge useful, this knowledge has to be interesting (i.e., it should have a potential value for the user; Han & Kamber, 2001).