DFKI-LT - Integrating Graded Knowledge and Temporal Change in a Modal Fragment of OWL
Integrating Graded Knowledge and Temporal Change in a Modal Fragment of OWL
1 Agents and Artificial Intelligence. Revised selected papers from the 8th International Conference, ICAART 2016,
Lecture Notes in Computer Science,
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.
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