Integrating Graded Knowledge and Temporal Change in a Modal Fragment of OWL

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• 刊名：Lecture Notes in Computer Science
• 出版年：2017
• 出版时间：2017
• 年：2017
• 卷：10162
• 期：1
• 页码：75-95
• 丛书名：Agents and Artificial Intelligence
• ISBN：978-3-319-53354-4
• 卷排序：10162

文摘

Natural language statements uttered in diagnosis, but more general in daily life are usually graded, i.e., are associated with a degree of uncertainty about the validity of an assessment and is often expressed through specific words in natural language. In this paper, we look into a representation of such graded statements by presenting a simple non-standard modal logic which comes with a set of modal operators, directly associated with the words indicating the uncertainty and interpreted through confidence intervals in the model theory. We complement the model theory by a set of RDFS-/OWL 2 RL-like entailment (if-then) rules, acting on the syntactic representation of modalized statements. After that, we extend the modal statements by transaction time, in order to implement a notion of temporal change. Our interest in such a formalization is related to the use of OWL as the de facto language in today’s ontologies and its weakness to represent and reason about assertional knowledge that is uncertain and that changes over time.