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Data Mining and the KDD Process

Data Mining and the KDD Process
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Author(s): Ana Funes (Universidad Nacional de San Luis, Argentina) and Aristides Dasso (Universidad Nacional de San Luis, Argentina)
Copyright: 2018
Pages: 15
Source title: Encyclopedia of Information Science and Technology, Fourth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-2255-3.ch167

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Abstract

Nowadays, there exists an increasing number of applications where analysis and discovery of new patterns have fueled the research and development of new methods, all related to Machine Learning, Knowledge Extraction, Knowledge Discovery in Databases or KDD, and Data Mining. The development of Data Mining and other related disciplines has benefited from the existence of large volumes of data proceeding from the most diverse sources and domains. KDD process and methods of Data Mining allows for the discovery of knowledge in data that is hidden to humans, presenting this knowledge under different ways. In this chapter, an overview of the KDD process with special focus in the phase of Data Mining is given. A discussion on Data Mining tasks and methods, a possible classification of them, the relation of Data Mining to other disciplines, and an overview of future challenges in the field are also given.

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