Skip to main content

A Possibilistic Logic Approach to Conditional Preference Queries

  • Conference paper
Flexible Query Answering Systems (FQAS 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8132))

Included in the following conference series:

Abstract

The paper presents a new approach to deal with database preference queries, where preferences are represented in the style of possibilistic logic, using symbolic weights. The symbolic weights may be processed without the need of a numerical assignment of priority. Still, it is possible to introduce a partial ordering among the symbolic weights if necessary. On this basis, four methods that have an increasing discriminating power for ranking the answers to conjunctive queries, are proposed. The approach is compared to different lines of research in preference queries including skyline-based methods and fuzzy set-based queries. With the four proposed ranking methods the first group of best answers is made of non dominated items. The purely qualitative nature of the approach avoids the commensurability requirement of elementary evaluations underlying the fuzzy logic methods.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Bosc, P., Pivert, O.: Some approaches for relational databases flexible querying. Journal of Intelligent Information Systems 1, 323–354 (1992)

    Article  Google Scholar 

  2. Fagin, R., Lotem, A., Naor, M.: Optimal aggregation algorithms for middleware. In: Proc. 20th ACM SIGACT-SIGMOD-SIGART Symp. on Principles of Database Syst. (2001)

    Google Scholar 

  3. Börzsönyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proc. 17th IEEE International Conference on Data Engineering, pp. 421–430 (2001)

    Google Scholar 

  4. Chomicki, J.: Preference formulas in relational queries. ACM Transactions on Database Systems 28, 1–40 (2003)

    Article  Google Scholar 

  5. Kiessling, W.: Foundations of preferences in database systems. In: Proc. of the 28th International Conference on Very Large Data Bases (VLDB 2002), pp. 311–322 (2002)

    Google Scholar 

  6. Boutilier, C., Brafman, R.I., Domshlak, C., Hoos, H., Poole, D.: CP-nets: A tool for representing and reasoning with conditional ceteris paribus preference statements. J. Artificial Intelligence Research (JAIR) 21, 135–191 (2004)

    MathSciNet  MATH  Google Scholar 

  7. Brafman, R.I., Domshlak, C.: Database preference queries revisited. Technical Report TR2004-1934, Cornell University, Computing and Information Science (2004)

    Google Scholar 

  8. HadjAli, A., Kaci, S., Prade, H.: Database preference queries - A possibilistic logic approach with symbolic priorities. Ann. Math. Artif. Intell. 63, 357–383 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  9. Bosc, P., Pivert, O., Prade, H.: A possibilistic logic view of preference queries to an uncertain database. In: Proc. IEEE Inter. Conf. on Fuzzy Systems (FUZZ-IEEE 2010), Barcelona, Spain, July 18-23, pp. 1–6 (2010)

    Google Scholar 

  10. Hadjali, A., Pivert, O., Prade, H.: On different types of fuzzy skylines. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds.) ISMIS 2011. LNCS, vol. 6804, pp. 581–591. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  11. Wilson, N.: Computational techniques for a simple theory of conditional preferences. Artif. Intell. 175, 1053–1091 (2011)

    Article  MATH  Google Scholar 

  12. Dubois, D., Prade, H.: Possibilistic logic: a retrospective and prospective view. Fuzzy Sets and Systems 144, 3–23 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  13. de Calmès, M., Dubois, D., Hüllermeier, E., Prade, H., Sedes, F.: Flexibility and fuzzy case-based evaluation in querying: An illustration in an experimental setting. Int. Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, 43–66 (2003)

    Article  MATH  Google Scholar 

  14. Benferhat, S., Dubois, D., Prade, H.: Towards a possibilistic logic handling of preferences. Applied Intelligence 14, 303–317 (2001)

    Article  MATH  Google Scholar 

  15. Dubois, D., Kaci, S., Prade, H.: Representing preferences in the possibilistic setting. In: Bosi, G., Brafman, R.I., Chomicki, J., Kies̈ling, W. (eds.) Preferences: Specification, Inference, Applications. Number 04271 in Dagstuhl Seminar Proceedings (2006)

    Google Scholar 

  16. Benferhat, S., Dubois, D., Kaci, S., Prade, H.: Bridging logical, comparative, and graphical possibilistic representation frameworks. In: Benferhat, S., Besnard, P. (eds.) ECSQARU 2001. LNCS (LNAI), vol. 2143, pp. 422–431. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  17. Benferhat, S., Dubois, D., Kaci, S., Prade, H.: Graphical readings of possibilisitc logic bases. In: 17th Conf. Uncertainty in AI (UAI 2001), Seattle, August 2-5, pp. 24–31 (2001)

    Google Scholar 

  18. Benferhat, S., Dubois, D., Garcia, L., Prade, H.: On the transformation between possibilistic logic bases and possibilistic causal networks. Inter. J. of Approx. Reas. 29, 135–173 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  19. Dubois, D., Prade, H., Touazi, F.: Conditional preference nets and possibilistic logic. In: van der Gaag, L.C. (ed.) ECSQARU 2013. LNCS, vol. 7958, pp. 181–193. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  20. Dubois, D., Prade, H., Touazi, F.: Handling partially ordered preferences in possibilistic logic. In: ECAI 2012 Workshop on Weighted Logics for Artificial Intelligence, pp. 91–98 (2012)

    Google Scholar 

  21. Benferhat, S., Yahi, S.: Complexity and cautiousness results for reasoning from partially preordered belief bases. In: Sossai, C., Chemello, G. (eds.) ECSQARU 2009. LNCS, vol. 5590, pp. 817–828. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  22. Yahi-Mechouche, S.: Raisonnement en présence d’incohérence: de la compilation de bases de croyances stratifiées à l’inférence à partir de bases de croyances partiellement préordonnées. Université d’Artois Faculté des Sciences Jean Perrin, Lens (2009)

    Google Scholar 

  23. Stefanidis, K., Koutrika, G., Pitoura, E.: A survey on representation, composition and application of preferences in database systems. ACM Trans. Database Syst. 36, 19:1–19:45 (2011)

    Google Scholar 

  24. Lacroix, M., Lavency, P.: Preferences: Putting more knowledge into queries. In: Proc. of the 13th Inter. Conference on Very Large Databases (VLDB 1987), pp. 217–225 (1987)

    Google Scholar 

  25. Bosc, P., Pivert, O.: Fuzzy Preference Queries to Relational Databases. Imperial College Press (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Dubois, D., Prade, H., Touazi, F. (2013). A Possibilistic Logic Approach to Conditional Preference Queries. In: Larsen, H.L., Martin-Bautista, M.J., Vila, M.A., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2013. Lecture Notes in Computer Science(), vol 8132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40769-7_33

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40769-7_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40768-0

  • Online ISBN: 978-3-642-40769-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics