Abstract
In this paper we discuss the challenges of performing reasoning on large scale RDF datasets from the Web. We discuss issues and practical solutions relating to reasoning over web data using a rule-based approach to forward-chaining; in particular, we identify the problem of ontology hijacking: new ontologies published on the Web re-defining the semantics of existing concepts resident in other ontologies. Our solution introduces consideration of authoritative sources. Our system is designed to scale, comprising of file-scans and selected lightweight on-disk indices. We evaluate our methods on a dataset in the order of a hundred million statements collected from real-world Web sources. © 2008 Springer Berlin Heidelberg.
Cite
CITATION STYLE
Hogan, A., Harth, A., & Polleres, A. (2008). SAOR: Authoritative reasoning for the Web. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5367 LNCS, pp. 76–90). https://doi.org/10.1007/978-3-540-89704-0_6
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