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缺乏容忍不一致能力的OWL算法

A Tableau Algorithm for Handling Inconsistency in OWL
课程网址: http://videolectures.net/eswc09_zhou_ataf/  
主讲教师: Liping Zhou
开课单位: 北京大学
开课时间: 2009-07-28
课程语种: 汉简
中文简介:
在语义Web中,知识源通常包含不一致性,因为它们不断变化并且来自不同的视点。众所周知,基于语义Web的描述逻辑,OWL缺乏容忍不一致或不完整数据的能力。最近,处理OWL不一致性的研究变得越来越重要。在本文中,我们提出了一种称为准经典OWL的超对称OWL来处理与保持重要推理规则(如模式收费,模态推理和析取三段论)不一致的问题。我们提出了一种可终止的,完整的,完整的画面算法,以在准经典OWL中实现次协调推理。与处理OWL不一致性的其他方法相比,我们的方法通过将次协调推理与重要的经典推理规则相结合来增强推理能力。
课程简介: In Semantic Web, the knowledge sources usually contain inconsistency because they are constantly changing and from different view points. As is well known, as based on the description logic of the Semantic Web, OWL is lack of the ability of tolerating inconsistent or incomplete data. Recently, the research in handling inconsistency in OWL becomes more and more important. In this paper, we present a paraconsistent OWL called quasi-classical OWL to handle inconsistency with holding important inference rules such as modus tollens, modus ponens, and disjunctive syllogism. We propose a terminable, sound and complete tableau algorithm to implement paraconsistent reasoning in quasi-classical OWL. In comparison with other approaches to handle inconsistency in OWL, our approach enhances the ability of reasoning by integrating paraconsistent reasoning with important classical inference rules.
关 键 词: 语义Web; 准经典OWL; 画面算法
课程来源: 视频讲座网
最后编审: 2019-04-13:lxf
阅读次数: 74