Bipolar Conjunctive Query Evaluation for Ontology Based Database Querying

  • Nouredine Tamani
  • Ludovic Liétard
  • Daniel Rocacher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8132)


In the wake of the flexible querying system, designed in [21], allowing the expression of user preferences as bipolar conditions of type “and if possible” over relational databases and ontologies, we detail in this paper the user query evaluation process, under the extension of the logical framework to bipolarity of type “or else” [15,14]. Queries addressed to our system are bipolar conjunctive queries made of bipolar atoms, and their evaluation relies on three-step algorithm: (i) atom substitution process that details how bipolar subsumption axioms defined in the bipolar ontology are used, (ii)query derivation process which delivers from each atom substitution a complementary query, and (iii) translation process that translates the obtained set of queries into bipolar SQLf statements, subsequently evaluated over a bipolar relational database.


Relational Database Relational Algebra Query Evaluation Conjunctive Query Coherence Property 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bordogna, G., Pasi, G.: A fuzzy query language with a linguistic hierarchical aggregator. In: Proc. of the ACM SAC 1994, pp. 184–187. ACM, USA (1994)CrossRefGoogle Scholar
  2. 2.
    Bosc, P., Pivert, O.: Sqlf: A relational database langage for fuzzy querying. IEEE Transactions on Fuzzy Systems 3(1), 1–17 (1995)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Bosc, P., Pivert, O., Liétard, L., Mokhtari, A.: Extending relational algebra to handle bipolarity. In: 25th ACM SAC, pp. 1717–1721 (2010)Google Scholar
  4. 4.
    Calvanese, D., Giacomo, G.D., Lembo, D., Lenzerini, M., Rosati, R.: Data complexity of query answering in description logics. In: KR, pp. 260–270 (2006)Google Scholar
  5. 5.
    Chomicki, J.: Querying with intrinsic preferences. In: Proceedings of the 8th International Conference on Extending Database Technology, pp. 34–51 (2002)Google Scholar
  6. 6.
    Colucci, S., Noia, T.D., Ragone, A., Ruta, M., Straccia, U., Tinelli, E.: Informative Top-k retrieval for advanced skill management. In: Semantic Web Information Management, ch. 19, pp. 449–476. Springer, Heidelberg (2010)Google Scholar
  7. 7.
    Dubois, D., Prade, H.: Bipolarity in flexible querying. In: Andreasen, T., Motro, A., Christiansen, H., Larsen, H.L. (eds.) FQAS 2002. LNCS (LNAI), vol. 2522, pp. 174–182. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  8. 8.
    Dubois, D., Prade, H.: Handling bipolar queries in fuzzy information processing. In: Handbook of Research on Fuzzy Information Processing in Databases, pp. 97–114. IGI Global (2008)Google Scholar
  9. 9.
    Dubois, D., Prade, H.: An introduction to bipolar representations of information and preference. Inter. Jour. of Intelligent Systems 23 (2008)Google Scholar
  10. 10.
    Dubois, D., Prade, H.: An overview of the asymmetric bipolar representation of positive and negative information in possibility theory. Fuzzy Sets and Systems 160(10), 1355–1366 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Kiesling, W.: Foundation of preferences in database systems. In: Proceedings of the 28th VLDB Conference, Hong Kong, China (2002)Google Scholar
  12. 12.
    Liétard, L., Rocacher, D.: On the definition of extended norms and co-norms to aggregate fuzzy bipolar conditions. In: IFSA/EUSFLAT, pp. 513–518 (2009)Google Scholar
  13. 13.
    Liétard, L., Rocacher, D., Bosc, P.: On the extension of sql to fuzzy bipolar conditions. In: 28th North American Information Processing Society Conference (2009)Google Scholar
  14. 14.
    Liétard, L., Rocacher, D., Tamani, N.: A relational algebra for generalized fuzzy bipolar conditions. In: Flexible Approaches in Data, Information and Knowledge Management. Springer (to appear, 2013)Google Scholar
  15. 15.
    Liétard, L., Tamani, N., Rocacher, D.: Fuzzy bipolar conditions of type ”or else”. In: FUZZ-IEEE, pp. 2546–2551 (2011)Google Scholar
  16. 16.
    Lorenz, B., Rosener, M.: Ontology of transportation networks. Tech. rep., REWERSE. Euro. Com. and Swiss Federal Office for Education and Science (2005)Google Scholar
  17. 17.
    Straccia, U.: Softfacts : a top-k retrieval engine for a tractable description logic accessing relational databases. Tech. rep., ISTI-CNR, Italy (Jan 2009)Google Scholar
  18. 18.
    Tamani, N.: Interrogation personnalisée des systémes d’information dédiés au transport: une approche bipolaire floue. Ph.D. thesis, Université de Rennes 1 (2012)Google Scholar
  19. 19.
    Tamani, N., Liétard, L., Rocacher, D.: Bipolar sQLf: A flexible querying language for relational databases. In: Christiansen, H., De Tré, G., Yazici, A., Zadrozny, S., Andreasen, T., Larsen, H.L. (eds.) FQAS 2011. LNCS, vol. 7022, pp. 472–484. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  20. 20.
    Tamani, N., Liétard, L., Rocacher, D.: Extension of an ontology for flexible querying. In: FUZZ-IEEE, pp. 2033–2038 (2011)Google Scholar
  21. 21.
    Tamani, N., Liétard, L., Rocacher, D.: A fuzzy ontology for database querying with bipolar preferences. Inter. Jour. of Intelligent Systems 28(1), 4–36 (2013)CrossRefGoogle Scholar
  22. 22.
    de Tré, G., Zadrozny, S., Bronselaer, A.: Handling bipolarity in elementary queries to possibilistic databases. IEEE Trans. on Fuzzy Systems 18(3), 599–612 (2010)CrossRefGoogle Scholar
  23. 23.
    De Tré, G., Zadrożny, S., Matthé, T., Kacprzyk, J., Bronselaer, A.: Dealing with positive and negative query criteria in fuzzy database querying. In: Andreasen, T., Yager, R.R., Bulskov, H., Christiansen, H., Larsen, H.L. (eds.) FQAS 2009. LNCS (LNAI), vol. 5822, pp. 593–604. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  24. 24.
    Zadeh, L.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)MathSciNetzbMATHCrossRefGoogle Scholar
  25. 25.
    Zadrożny, S., Kacprzyk, J.: Bipolar queries: A way to enhance the flexibility of database queries. In: Ras, Z.W., Dardzinska, A. (eds.) Advances in Data Management. SCI, vol. 223, pp. 49–66. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nouredine Tamani
    • 1
  • Ludovic Liétard
    • 2
  • Daniel Rocacher
    • 3
  1. 1.IATE/INRA-SupagroFrance
  2. 2.IRISA/IUT/Univ. Rennes 1France
  3. 3.IRISA/ENSSAT/Univ. Rennes 1France

Personalised recommendations