Reasoning within Fuzzy Description Logics
Reasoning within Fuzzy Description Logics
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DOI：
10.1613/jair.813
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发表时间：
2011-06
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影响因子：
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通讯作者：
U. Straccia
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文献类型：
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作者：
U. Straccia
描述逻辑（dl）是一种适用于管理结构化知识的、众所周知的逻辑。它们允许对个体和定义良好的概念进行推理，即具有共同属性的个体集。在应用程序中使用dl的经验表明，在许多情况下，我们希望扩展它们的功能。特别是，它们在多媒体信息检索（MIR）上下文中的使用使人们相信，这样的dl应该允许处理多媒体对象内容表示和检索中固有的不精确性。本文将结合Zadeh的模糊逻辑与经典深度学习，提出ALC的模糊扩展。特别是，概念变得模糊，因此支持对不精确概念的推理。我们将定义它的语法，语义，描述它的属性，并提出一个约束传播演算来进行推理。
Description Logics (DLs) are suitable, well-known, logics for managing structured knowledge. They allow reasoning about individuals and well defined concepts, i.e. set of individuals with common properties. The experience in using DLs in applications has shown that in many cases we would like to extend their capabilities. In particular, their use in the context of Multimedia Information Retrieval (MIR) leads to the convincement that such DLs should allow the treatment of the inherent imprecision in multimedia object content representation and retrieval. In this paper we will present a fuzzy extension of ALC, combining Zadeh's fuzzy logic with a classical DL. In particular, concepts becomes fuzzy and, thus, reasoning about imprecise concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.