Formal ontology, conceptual analysis and knowledge representation

Formal ontology, conceptual analysis and knowledge representation
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DOI:
10.1006/ijhc.1995.1066
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发表时间:
1995-11-01
影响因子:
5.4
通讯作者:
Guarino, N
Guarino, N
中科院分区:
计算机科学2区
文献类型:
--
作者:
Guarino, N

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本文的目的是捍卫当前知识工程实践中形式本体论原理的系统引入,探索本体论和知识表示之间的各种关系,并展示这一有前途的研究领域的最新趋势。根据克兰西提出的知识获取的“建模观点”,建模活动必须在知识库和两个独立的子系统之间建立对应关系:主体的行为(即解决问题的专业知识)和其自身的环境(问题域)。当前的知识建模方法往往只关注前一个子系统,将领域知识视为强烈依赖于手头的特定任务:事实上,人工智能研究人员似乎对推理的本质而不是现实世界的本质更感兴趣。然而,最近,适合大规模集成的独立于任务的知识库(或“本体论”)的潜在价值已在许多方面得到强调。在本文中,我们将推理和表示之间的二分法与认识论和本体论之间的哲学区别进行比较。我们引入了本体论层面的概念,它介于布拉克曼讨论的认识论和概念层面之间,作为描述知识表示形式主义的一种方式,同时考虑到其原语的预期含义。然后我们讨论一些正式的本体论区别,它们可能为此目的发挥重要作用。 (C) 1995 学术出版社有限公司
The purpose of this paper is to defend the systematic introduction of formal ontological principles in the current practice of knowledge engineering, to explore the various relationships between ontology and knowledge representation, and to present the recent trends in this promising research area. According to the ''modelling view'' of knowledge acquisition proposed by Clancey, the modelling activity must establish a correspondence between a knowledge base and two separate subsystems: the agent's behaviour (i.e. the problem-solving expertise) and its own environment (the problem domain). Current knowledge modelling methodologies tend to focus on the former sub-system only, viewing domain knowledge as strongly dependent on the particular task at hand: in fact, AI researchers seem to have been much more interested in the nature of reasoning rather than in the nature of the real world. Recently, however, the potential value of task-independent knowledge bases (or ''ontologies'') suitable to large scale integration has been underlined in many ways.In this paper, we compare the dichotomy between reasoning and representation to the philosophical distinction between epistemology and ontology. We introduce the notion of the ontological level, intermediate between the epistemological and the conceptual levels discussed by Brachman, as a way to characterize a knowledge representation formalism taking into account the intended meaning of its primitives. We then discuss some formal ontologic distinctions which may play an important role for such purpose. (C) 1995 Academic Press Limited