An Approach to Representing Uncertainty Rules in RuleML.
In Proceedings of the 2nd International Conference on Rules and Rule Markup Languages for the Semantic Web (RuleML-06), 2006.
Abstract:
The RuleML initiative defines a normalized markup for expressing and exchange rules in the Semantic Web. However, the syntax of the language is still limited and lacks features for representing rule-based languages capable of handling uncertainty. It is desirable to have a general extension of RuleML which accommodates major existing languages proposed in the latest two decades. The main contribution of the paper is to propose such a general extension, showing how to encode many of the existing languages in this extension. We hope this work can also provide some insights on how to cover uncertainty in the RIF framework.