The knowledge discovery process is as old as Homo sapiens. Until some time ago this process was solely based on the 'natural personal' computer provided by Mother Nature. Fortunately, in recent decades the problem has begun to be solved based on the development of the Data mining technology, aided by the huge computational power of the 'artificial' computers. Digging intelligently in different large databases, data mining aims to extract implicit, previously unknown and potentially useful information from data, since "knowledge is power". The goal of this book is to provide, in a friendly way, both theoretical concepts and, especially, practical techniques of this exciting field, ready to be applied in real-world situations. Accordingly, it is meant for all those who wish to learn how to explore and analysis of large quantities of data in order to discover the hidden nugget of information.
From the reviews:
"Provides a gentle introduction to a fascinating and emerging research area. ... provide an easy-to-read 'compass' to lead readers though the basic principles. ... material presented is comprehensive and covers every aspect of data mining. ... Ample examples give readers an appreciation for how the methodologies can be applied in real-life situations ... . bibliography will help those interested in obtaining further information on the topic. This book is ideal for students ... . Summing Up: Highly recommended. Lower-division undergraduates and two-year technical program students." (J. Y. Cheung, Choice, Vol. 49 (4), December, 2011)
"Provides a gentle introduction to a fascinating and emerging research area. ... provide an easy-to-read 'compass' to lead readers though the basic principles. ... material presented is comprehensive and covers every aspect of data mining. ... Ample examples give readers an appreciation for how the methodologies can be applied in real-life situations ... . bibliography will help those interested in obtaining further information on the topic. This book is ideal for students ... . Summing Up: Highly recommended. Lower-division undergraduates and two-year technical program students." (J. Y. Cheung, Choice, Vol. 49 (4), December, 2011)