一种可移植本体规范的翻译方法

Thomas R. Gruber
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引用次数: 13627

摘要

为了支持在人工智能系统之间共享和重用形式化表示的知识,定义表示共享知识的通用词汇表是有用的。为共享的话语领域——类、关系、函数和其他对象的定义——指定一个代表性词汇表被称为本体论。本文描述了一种用于定义在表示系统上可移植的本体的机制。以谓词演算标准格式编写的定义由一个名为Ontolingua的系统翻译成专门的表示,包括基于框架的系统和关系语言。这允许研究人员共享和重用本体,同时保留专门实现的计算优势。我们讨论了可移植性的翻译方法如何解决几个技术问题。一个问题是如何在保留声明性内容的同时适应表示之间的风格和组织差异。另一个问题是如何从一种表达能力很强的语言翻译成受限制的语言,保持系统独立性,同时保持实现系统的计算效率。我们描述了如何通过将Ontolingua本身建立在与领域无关的、具有代表性的习语的本体之上来解决这些问题。
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A translation approach to portable ontology specifications

To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse—definitions of classes, relations, functions, and other objects—is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations.

We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms.

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