摘要翻译：
描述逻辑(DLs)是管理结构化知识的合适的、众所周知的逻辑。它们允许对个体和定义明确的概念进行推理，即具有共同属性的个体集合。在应用程序中使用DLs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)中的应用使人们相信，这种DLs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Zadeh的模糊逻辑与经典DL相结合，给出了ALC的模糊扩展。特别是，概念变得模糊，因此支持关于不精确概念的推理。我们将定义它的语法、语义，描述它的性质，并给出一个用于推理的约束传播演算。
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英文标题：
《Reasoning within Fuzzy Description Logics》
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作者：
U. Straccia
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  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.
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PDF链接：
https://arxiv.org/pdf/1106.0667