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

机译:一种基于遗传模糊系统的知识发现方法,用于获取消费者的行为模式。基于Web的信任模型的经验应用

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摘要

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.
机译:本文显示了一项较大的跨学科研究的一部分,该研究专注于开发基于人工智能的分析工具,以帮助营销经理在消费者市场上做出决策。特别是,在此介绍并测试了一种基于遗传模糊系统的知识发现方法-一种将模糊逻辑和遗传算法结合起来的软计算(SC)方法-将用于营销建模。它的特征与市场经理当前对市场分析方法的要求非常一致。具体而言,已经引起人们的注意,以详细说明该提议的(数据库中的知识发现)KDD方法如何在基于Web的信任消费者模型的经验应用中执行。

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