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Data Mining with Graphical Models

机译:数据挖掘与图形模型

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摘要

The explosion of data stored in commercial or administrational databases calls for intelligent techniques to discover the patterns hidden in them and thus to exploit all available information. Therefore a new line of research has recently been established, which became known under the names "Data Minning" and "Knowledge Discovery in Databases". In this paper we study a popular technique from its arsenal of methods to do dependency analysis, namely learning inferene networks (also called "graphical models") from data. We review the already well-known probabilistic networks and provide an introduction to the recently developed and closely related possibilistic networks.
机译:存储在商业或管理数据库中的数据的爆炸要求智能技术来发现隐藏在其中的模式,从而利用所有可用信息。因此,最近已经建立了新的研究系列,这在名称“数据挖掘”和“数据库中的知识发现”中已知。在本文中,我们研究了从其依赖性分析的方法中的流行技术,即学习中文网络(也称为“图形模型”)从数据中进行学习。我们审查了已知的概率网络,并提供了最近开发和密切相关的可能性网络的介绍。

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