Skip to main content

Optimizing Fixpoint Evaluation of Logic Programs with Uncertainty

  • Conference paper
Advances in Computer Science and Engineering (CSICC 2008)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 6))

Included in the following conference series:

Abstract

We investigate efficient techniques for bottom-up, fixpoint evaluation of logic programs and deductive databases with uncertainty over the certainty domain [0,1], often assumed to be a complete lattice ordered by ≤ with min and max as the meet and join operators, respectively. Standard evaluation methods are inadequate in our context in particular when multiset is used as the semantics structure and when programs use aggregate functions other than the lattice join. We propose a semi-naïve method which adopts and extends relation partitioning and backtracking techniques used in standard case. We developed a running prototype of our method, called SNPB, and studied its performance. Our experimental results indicated a speed-up gain, over the semi-naïve method, ranging from 1.25 to 203, depending on the structures and sizes of the input data set and the programs.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Abiteboul, S., et al.: The Lowell Database Research Self-Assessment. Communication of the ACM 48(15), 111–118 (2005)

    Article  Google Scholar 

  2. Beeri, C., Ramakrishnan, R.: On the Power of Magic. J. of Logic Programming 10, 255–299 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  3. Ceri, S., Gottlob, G., Tanca, L.: What You Always Wanted to Know About Datalog (and Never Dared to Ask). IEEE TKDE 1(1), 146–166 (1989)

    Google Scholar 

  4. Dubois, D., Lang, J., Prade, H.: Towards Possibilistic Logic Programming. In: 10th International Conference on Logic Programming, pp. 581–595 (1991)

    Google Scholar 

  5. Kifer, M., Li, A.: On the Semantics of Rule-Based Expert Systems with Uncertainty. In: 2nd ICDT, pp. 102–117 (1988)

    Google Scholar 

  6. Kifer, M., Subrahmanian, V.S.: Theory of Generalized Annotated Logic Programming and its Applications. Journal of Logic Programming 12(3&4), 335–367 (1992)

    Article  MathSciNet  Google Scholar 

  7. Kuittinen, J., Nurmi, O., Sippu, S., Soininen, E.S.: Efficient Implementation of Loops in Bottom-up Evaluations of Logic Queries. In: 16th International Conference on Very Large Data Bases Conference, Queensland, Australia, pp. 372–379 (1990)

    Google Scholar 

  8. Lakshmanan, L.V.S., Sadri, F.: Probabilistic Deductive Databases. In: Symp. on Logic Programming, pp. 254–268 (1994)

    Google Scholar 

  9. Lakshmanan, L.V.S., Sauri, F.: Modeling Uncertainty in Deductive Databases. In: Karagiannis, D. (ed.) DEXA 1994. LNCS, vol. 856, pp. 724–733. Springer, Heidelberg (1994)

    Chapter  Google Scholar 

  10. Lakshmanan, L.V.S., Shiri, N.: A Parametric Approach to Deductive Databases with Uncertainty. IEEE TKDE 13, 554–574 (2001)

    Google Scholar 

  11. Leach, S.M., Lu, J.J.: Query Processing in Annotated Logic Programming: Theory and Implementation. Journal of Intelligent Information Systems 6(1), 33–58 (1996)

    Article  Google Scholar 

  12. Lloyd, J.W.: Foundations of Logic Programming, 2nd edn. Springer, Heidelberg (1987)

    Book  MATH  Google Scholar 

  13. Ng, R.T., Subrahmanian, V.S.: Probabilistic Logic Programming. Information and Computation 101(2), 150–201 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  14. Ramakrishnan, R., Srivastava, D., Sudarshan, S., Seshadri, P.: The CORAL Deductive System. VLDB Journal 3(2), 161–210 (1994)

    Article  Google Scholar 

  15. Ramakrishnan, R., Ullman, J.D.: A Survey of Deductive Database Systems. Journal of Logic Programming 23(2), 125–149 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  16. Sagonas, K.F., Swift, T., Warren, D.S.: XSB as an Efficient Deductive Database Engine. In: SIGMOD Conference, pp. 442–453 (1994)

    Google Scholar 

  17. Shiri, N.: Expressive Power of Logic Frameworks with Uncertainty. In: 18th Int’l FLAIRS Conference, Special Track on Uncertainty Reasoning, Florida, May 16–18 (2005)

    Google Scholar 

  18. Shiri, N., Zheng, Z.: Challenges in Fixpoint Computation with Multisets. In: International Symposium on Foundations of Information and Knowledge Systems, pp. 273–290 (2004)

    Google Scholar 

  19. Van Emden, M.H.: Quantitative Deduction and Its Fixpoint Theory. Journal of Logic Programming 4, 37–53 (1986)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Shiri, N., Zheng, Z.H. (2008). Optimizing Fixpoint Evaluation of Logic Programs with Uncertainty. In: Sarbazi-Azad, H., Parhami, B., Miremadi, SG., Hessabi, S. (eds) Advances in Computer Science and Engineering. CSICC 2008. Communications in Computer and Information Science, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89985-3_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89985-3_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89984-6

  • Online ISBN: 978-3-540-89985-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics