A knowledge discovery method based on genetic-fuzzy systems for obtaining consumer behaviour patterns. An empirical application to a Web-based trust model

A knowledge discovery method based on genetic-fuzzy systems for obtaining consumer behaviour patterns. An empirical application to a Web-based trust model

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Article ID: iaor200969066
Country: United Kingdom
Volume: 10
Issue: 5/6
Start Page Number: 402
End Page Number: 428
Publication Date: Jun 2009
Journal: International Journal of Management and Decision Making
Authors: ,
Keywords: knowledge management, behaviour
Abstract:

This paper shows part of a larger interdisciplinary research focused on developing artificial intelligence-based analytical tools to aid the marketing managers' decisions on consumer markets. In particular, here it is presented and tested a knowledge discovery methodology based on genetic-fuzzy systems – a Soft Computing (SC) method that jointly makes use of fuzzy logic and genetic algorithms – to be applied in marketing modelling. Its characteristics are very coherent with the requirements that marketing managers currently demand to market analytical methods. Specifically, it has been paid attention to illustrate, in detail, how this proposed (Knowledge Discovery in Databases) KDD method performs with an empirical application to a Web-based trust consumer model.

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