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Based on practical observations on rule-based inference on RDF data, the authors study the problem of redundancy elimination on RDF graphs in the presence of rules (in the form of Datalog rules) and constraints, (in the form of so-called tuple-generating dependencies), and with respect to queries (ranging from conjunctive queries up to more complex ones, particularly covering features of SPARQL, such as union, negation, or filters). To this end, they investigate the influence of several problem parameters (like restrictions on the size of the rules, the constraints, and/or the queries) on the complexity of detecting redundancy. The main result of this paper is a fine-grained complexity analysis of both graph and rule minimisation in various settings.
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