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Semi-structured Decision Rules in Object-Oriented Rough Set Models for Kansei Engineering

机译:关西工程面向对象的粗糙集模型中的半结构化决策规则

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Decision rule generation from Kansei data using rough set theory is one of the most hot topics in Kansei engineering. Usually, Kansei data have various types of scheme, however, Pawlak's "traditional" rough set theory treats structured data mainly, that is, decision tables with fixed attributes and no hierarchy among data. On the other hand, Kudo and Murai have proposed the object-oriented rough set model which treats structural hierarchies among objects. In this paper, we propose semi-structured decision rules in the object-oriented rough set model to represent structural characteristics among objects, which enable us to consider characteristics of hierarchical data by rough sets.
机译:使用粗糙集理论从Kansei数据生成决策规则是Kansei工程中最热门的主题之一。通常,Kansei数据具有各种类型的方案,但是,Pawlak的“传统”粗糙集理论主要处理结构化数据,即具有固定属性且数据之间没有层次的决策表。另一方面,工藤和村来提出了一种面向对象的粗糙集模型,该模型处理对象之间的结构层次。在本文中,我们提出了面向对象的粗糙集模型中的半结构化决策规则来表示对象之间的结构特征,这使我们能够通过粗糙集来考虑分层数据的特征。

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