由感知系统诱导的信息颗粒系统

Anna Bryniarska
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引用次数: 0

摘要

语义网络,特别是语义网中表示的知识,可以用属性语言ai来表达。这种语言的表达可以用不同的信息颗粒理论来解释:集合论、概率论、证据系统中的可能数据集、阴影集、模糊集或粗糙集。为了统一不同理论对表达式的解释,假设可以在一个被称为颗粒系统的关系系统中解释$AL$语言的表达式。本文提出了使用信息颗粒数据库,并论证了该数据库可以由信息检索充分性的度量系统——感知系统所诱导。它可以大大简化以前对信息颗粒系统的形式化描述。本文还给出了一些用感知系统诱导粗糙和模糊颗粒数据库的例子。
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Information granule system induced by a perceptual system
Knowledge represented in the semantic network, especially in the Semantic Web, can be expressed in attributive language AL. Expressions of this language are interpreted in different theories of information granules: set theory, probability theory, possible data sets in the evidence systems, shadowed sets, fuzzy sets or rough sets. In order to unify the interpretations of expressions for different theories, it is assumed that expressions of the $AL$ language can be interpreted in a chosen relational system called a granule system. In this paper, it is proposed to use information granule database and it is also demonstrated that this database can be induced by the measurement system of the adequacy of information retrieval, called a perceptual system. It can simplify previous formal description of the information granule system significantly. This paper also shows some examples of inducing rough and fuzzy granule databases by some perceptual systems.
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