Analyzing the AIR Language: A Semantic Web (Production) Rules Language
Authors
Hendler, James A.
Khandelwal, Ankesh
Bao, Jie
Kagal, Lalana
Jacobi, Ian
Ding, Li
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Issue Date
2010-01-01
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Abstract
The Accountability In RDF (AIR) language is an N3-based, Semantic Web production rule language that supports nested activation of rules, negation, closed world reasoning, scoped contextualized reasoning, and explanation of inferred facts. Each AIR rule has unique identifier (typically an HTTP URI) that supports reuse of rule. In this paper we analyze the semantics of AIR language by: i) giving the declarative semantics that support the reasoning algorithm, ii) providing complexity of AIR inference; and iii) evaluating the expressiveness of language by encoding Logic Programs of different expressivities in AIR.