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Quantitative
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10.1142/9789814407724_0017

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532pp
Dec 2012

ISBN: 978-981-4407-71-7 (hardcover)

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Quantitative Modelling in Marketing and Management

edited by: Luiz Moutinho (University of
Glasgow, UK) edited by: Kun-Huang Huarng (Feng Chia University,
Taiwan)

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DATA
MINING PROCESS MODELS: A ROADMAP FOR KNOWLEDGE DISCOVERY

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Armando B. Mendes,
Luís Cavique, and Jorge
M.A. Santos (2012) DATA MINING PROCESS MODELS:
A ROADMAP FOR KNOWLEDGE DISCOVERY. Quantitative Modelling in
Marketing and Management: pp. 405-433.

doi: 10.1142/9789814407724_0017

PART 3. MATHEMATICAL AND OTHER MODELS

DATA MINING PROCESS MODELS: A ROADMAP FOR
KNOWLEDGE DISCOVERY

Armando B. Mendes

Universidade Açores, Portugal
Luís
Cavique

Universidade Aberta, Portugal
Jorge
M.A. Santos

Universidade Évora, Portugal

Data mining applications are common for quantitative modelling management
problems resolution. As their learning curve has been very much simplified, is
no surprise that many users try to apply data mining methods to data bases in a
non-planned way. In this chapter, the CRISP-DM process model methodology is
presented with the intention of avoiding common traps in data mining
applications utilization. The use of this methodology is exemplified with
serveral cases of application developed by the authors.

Keywords: Data mining; process model; CRISP-DM

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