Advertisement

A Variant of Earley Deduction with Partial Evaluation

  • Stefan Brass
  • Heike Stephan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7994)

Abstract

We present an algorithm for query evaluation given a logic program consisting of function-free Datalog rules. The algorithm is based on Earley Deduction [7,10], but uses explicit states to eliminate rules which are no longer needed, and partial evaluation to minimize the work at runtime. At least in certain cases, the new method is more efficient than our SLDMagic-method [2], and also beats the standard Magic set method. It is also theoretically interesting, because it consumes one EDB fact in each step. Because of its origin, it is especially well suited for parsing applications, e.g. for extracting data from web pages. However, it has the potential to speed up basic Datalog reasoning for many semantic web applications.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Angles, R., Gutierrez, C.: The expressive power of SPARQL. In: Sheth, A., Staab, S., Dean, M., Paolucci, M., Maynard, D., Finin, T., Thirunarayan, K. (eds.) ISWC 2008. LNCS, vol. 5318, pp. 114–129. Springer, Heidelberg (2008), http://www.dcc.uchile.cl/cgutierr/papers/expPowSPARQL.pdf CrossRefGoogle Scholar
  2. 2.
    Brass, S.: SLDMagic — the real magic (With applications to web queries). In: Lloyd, J., et al. (eds.) CL 2000. LNCS (LNAI), vol. 1861, pp. 1063–1077. Springer, Heidelberg (2000), http://link.springer.com/chapter/10.1007%2F3-540-44957-4_71 CrossRefGoogle Scholar
  3. 3.
    Brass, S.: Implementation alternatives for bottom-up evaluation. In: Hermenegildo, M., Schaub, T. (eds.) Technical Communications of the 26th International Conference on Logic Programming (ICLP 2010). Leibniz International Proceedings in Informatics (LIPIcs), vol. 7, pp. 44–53. Schloss Dagstuhl (2010), http://drops.dagstuhl.de/opus/volltexte/2010/2582
  4. 4.
    Brass, S.: Order in datalog with applications to declarative output. In: Barceló, P., Pichler, R. (eds.) Datalog 2.0 2012. LNCS, vol. 7494, pp. 56–67. Springer, Heidelberg (2012), http://users.informatik.uni-halle.de/~brass/order/ CrossRefGoogle Scholar
  5. 5.
    Bry, F., Furche, T., Ley, C., Marnette, B., Linse, B., Schaffert, S.: Datalog relaunched: Simulation unification and value invention. In: de Moor, O., Gottlob, G., Furche, T., Sellers, A. (eds.) Datalog 2010. LNCS, vol. 6702, pp. 321–350. Springer, Heidelberg (2011), http://link.springer.com/chapter/10.1007%2F978-3-642-24206-9_19 CrossRefGoogle Scholar
  6. 6.
    Calì, A., Gottlob, G., Lukasiewicz, T.: A general Datalog-based framework for tractable query answering over ontologies. In: Proc. of the 28th ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS 2009), pp. 77–86. ACM (2009), http://dx.doi.org/10.1145/1559795.1559809
  7. 7.
    Pereira, F.C.N., Warren, D.H.D.: Parsing as deduction. In: Proceedings of the 21st Annual Meeting of the Association for Computational Linguistics (ACL), pp. 137–144 (1983), http://www.aclweb.org/anthology/P83-1021
  8. 8.
    Polleres, A.: From SPARQL to rules (and back). In: Proceedings of the Sixteenth International World Wide Web Conference (WWW 2007), pp. 787–796 (2007), http://wwwconference.org/www2007/papers/paper435.pdf
  9. 9.
    Polleres, A.: How (well) do Datalog, SPARQL and RIF interplay? In: Barceló, P., Pichler, R. (eds.) Datalog 2.0 2012. LNCS, vol. 7494, pp. 27–30. Springer, Heidelberg (2012), http://link.springer.com/chapter/10.1007/978-3-642-32925-8_4 CrossRefGoogle Scholar
  10. 10.
    Porter III, H.H.: Earley deduction (1986), http://web.cecs.pdx.edu/~harry/earley/earley.pdf

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Stefan Brass
    • 1
  • Heike Stephan
    • 1
  1. 1.Institut für InformatikMartin-Luther-Universität Halle-WittenbergHalle (Saale)Germany

Personalised recommendations