Abstract
In recent years, probabilistic models for Resource Description Framework (RDF) and its extension RDF Schema (RDFS) have been proposed to encode probabilistic knowledge. The probabilistic knowledge encoded by these models ranges from statistical relationships over possible objects of an RDF triple to relationships among correlated triples. The types of queries executed on these models vary from single triple patterns to complex graph patterns written in SPARQL, a W3C query language for RDF. Some query answerings only include reasoning of transitive properties and others do not have any reasoning. In this paper, we propose answering SPARQL queries with RDFS reasoning on probabilistic models that encode statistical relationships among correlated triples. One result to note is that although uncertainties of explicitly declared triples are specified using point probabilities, the evaluation of answers involving derived triples results in interval probabilities. Moreover, we experimentally examine how the execution time of the proposed query answering scales with the data size and the percentage of probabilistic triples in the data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Carroll, J.J., Dickinson, I., Dollin, C., Reynolds, D., Seaborne, A., Wilkinson, K.: Jena: implementing the semantic web recommendations. In: Feldman, S.I., Uretsky, M., Najork, M., Wills, C.E. (eds.) WWW (Alternate Track Papers & Posters), pp. 74–83. ACM, New York (2004)
Guo, Y., Pan, Z., Heflin, J.: An evaluation of knowledge base systems for large OWL datasets. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 274–288. Springer, Heidelberg (2004)
Huang, H., Liu, C.: Query evaluation on probabilistic RDF databases. In: Vossen, G., Long, D.D.E., Yu, J.X. (eds.) WISE 2009. LNCS, vol. 5802, pp. 307–320. Springer, Heidelberg (2009)
Kalyanpur, A.: Debugging and repair of OWL ontologies. Ph.D. thesis, University of Maryland at College Park, College Park, MD, USA (2006)
Karp, R.M., Luby, M., Madras, N.: Monte-carlo approximation algorithms for enumeration problems. Journal of Algorithms 10(3), 429–448 (1989)
OWL 2 web ontology language, http://www.w3.org/TR/owl2-overview/
Resource description framework (RDF), http://www.w3.org/RDF/
SPARQL query language for RDF, http://www.w3.org/TR/rdf-sparql-query/
Szeto, C.C., Hung, E., Deng, Y.: Modeling and querying probabilistic RDFS data sets with correlated triples. In: Du, X., Fan, W., Wang, J., Peng, Z., Sharaf, M.A. (eds.) APWeb 2011. LNCS, vol. 6612, pp. 333–344. Springer, Heidelberg (2011)
Szeto, C.C., Hung, E., Deng, Y.: Modeling and querying probabilistic RDFS data sets with correlated triples (extended version), technical report, The Hong Kong Polytechnic University (2011), http://www.comp.polyu.edu.hk/~csccszeto/publications/prdfs_tr.pdf
Udrea, O., Subrahmanian, V.S., Majkic, Z.: Probabilistic RDF. In: IRI, pp. 172–177. IEEE Systems, Man, and Cybernetics Society (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Szeto, CC., Hung, E., Deng, Y. (2011). SPARQL Query Answering with RDFS Reasoning on Correlated Probabilistic Data. In: Wang, H., Li, S., Oyama, S., Hu, X., Qian, T. (eds) Web-Age Information Management. WAIM 2011. Lecture Notes in Computer Science, vol 6897. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23535-1_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-23535-1_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23534-4
Online ISBN: 978-3-642-23535-1
eBook Packages: Computer ScienceComputer Science (R0)