扩展的RDF作为规则置标语言的语义基础
Extended RDF as a Semantic Foundation of Rule Markup Languages
摘要：
本体论和自动推理是语义网的基础。派生规则可以被包括在本体中以基于基本概念来定义派生概念。例如，规则允许基于相同或其他类和属性的扩展之间的复杂关系来定义类或属性的扩展。另一方面，也需要包括否定失败和明确否定信息的形式的否定信息，以实现各种形式的推理。在本文中，我们扩展了RDF图的弱否定和强否定，以及派生规则。定义了扩展框架（Extended RDF）的ERDF稳定模型语义，扩展了RDF（S）语义。我们的理论的一个显着特点，这是基于部分逻辑，是真和假的属性和类的扩展被认为是，允许真值差距。我们的框架支持封闭世界和开放世界的推理，通过明确表示特定的封闭世界的假设和ERDF本体论类别的总属性和总类。
英文摘要：
Ontologies and automated reasoning are the building blocks of the Semantic Web initiative. Derivation rules can be included in an ontology to define derived concepts, based on base concepts. For example, rules allow to define the extension of a class or property, based on a complex relation between the extensions of the same or other classes and properties. On the other hand, the inclusion of negative information both in the form of negation-as-failure and explicit negative information is also needed to enable various forms of reasoning. In this paper, we extend RDF graphs with weak and strong negation, as well as derivation rules. The ERDF stable model semantics of the extended framework (Extended RDF) is defined, extending RDF(S) semantics. A distinctive feature of our theory, which is based on Partial Logic, is that both truth and falsity extensions of properties and classes are considered, allowing for truth value gaps. Our framework supports both closed-world and open-world reasoning through the explicit representation of the particular closed-world assumptions and the ERDF ontological categories of total properties and total classes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
