Relaxed Safeness in Datalog-Based Policies

This paper presents a safeness condition that is more liberal than the one commonly imposed on Datalog, based on classifying predicate arguments into input and output arguments, thereby extending the expressiveness of Datalog-based policy languages. It is also shown that the relaxed safeness condition is a powerful tool for adding important features to such languages.

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In  5th International Symposium on Linked Rules (RuleML)

Publisher  Springer

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TypeInproceedings
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