Algebraic Optimization of Relational Queries with Various Kinds of Preferences

  • Radim Nedbal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4910)


Preferences can be used for information filtering and extraction to deliver the most relevant data to the user. Therefore the efficient integration of querying with preferences into standard database technology is an important issue. The paper resumes a logical framework for formulating preferences and their embedding into relational algebra through a single preference operator parameterized by a set of user preferences of sixteen various kinds and returning only the most preferred subsets of its argument relation. Most importantly, preferences between sets of elements can be expressed. To make a relational query language with the preference operator useful for practical applications, formal foundation for algebraic optimization, applying heuristics like push preference, has to be provided. Therefore abstract properties of the preference operator and a variety of algebraic laws describing its interaction with other relational algebra operators are presented.


logic of preference relational query optimization 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kießling, W.: Foundations of Preferences in Database Systems. In: Proceedings of the 28th VLDB Conference, Hong Kong, China, pp. 311–322 (2002)Google Scholar
  2. 2.
    Kießling, W., Hafenrichter, B.: Algebraic optimization of relational preference queries. Technical Report 2003-01, Institute of Computer Science, University of Augsburg (February 2003)Google Scholar
  3. 3.
    Chomicki, J.: Preference Formulas in Relational Queries. ACM Trans. Database Syst. 28(4), 427–466 (2003)CrossRefGoogle Scholar
  4. 4.
    Börzsönyi, S., Kossmann, D., Stocker, K.: The skyline operator. In: Proceedings of the 17th International Conference on Data Engineering, pp. 421–430. IEEE Computer Society, Washington, DC, USA (2001)CrossRefGoogle Scholar
  5. 5.
    von Wright, G.: The logic of preference. Edinburgh University Press, Edinburgh (1963)Google Scholar
  6. 6.
    Doyle, J., Wellman, M.P.: Representing preferences as ceteris paribus comparatives. In: Decision-Theoretic Planning: Papers from the 1994 Spring AAAI Symposium, pp. 69–75. AAAI Press, Menlo Park, California (1994)Google Scholar
  7. 7.
    Kaci, S., van der Torre, L.W.N.: Non-monotonic reasoning with various kinds of preferences. In: Brafman, R.I., Junker, U. (eds.) IJCAI 2005. Multidisciplinary Workshop on Advances in Preference Handling, pp. 112–117 (2005)Google Scholar
  8. 8.
    Lacroix, M., Lavency, P.: Preferences; Putting More Knowledge into Queries. In: Stocker, P.M., Kent, W., Hammersley, P. (eds.) VLDB, pp. 217–225. Morgan Kaufmann, San Francisco (1987)Google Scholar
  9. 9.
    Govindarajan, K., Jayaraman, B., Mantha, S.: Preference datalog. Technical Report 95-50 (January 1995)Google Scholar
  10. 10.
    Hafenrichter, B., Kießling, W.: Optimization of relational preference queries. In: CRPIT ’39. Proceedings of the sixteenth Australasian conference on Database technologies, Darlinghurst, pp. 175–184. Australian Computer Society, Inc., Australia (2005)Google Scholar
  11. 11.
    Nedbal, R.: Relational Databases with Ordered Relations. Logic Journal of the IGPL 13(5), 587–597 (2005)CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Radim Nedbal
    • 1
  1. 1.Institute of Computer Science, Academy of Sciences of the Czech RepublicCzech Republic

Personalised recommendations