Skip to main content
SpringerLink
Log in

Flexible Bipolar Querying of Uncertain Data Using an Ontology

  • Chapter
  • First Online:
Flexible Approaches in Data, Information and Knowledge Management

Part of the book series: Studies in Computational Intelligence ((SCI,volume 497))

Abstract

In this chapter, we propose an approach to query a database where the user preferences can be bipolar (i.e., express both constraints and wishes about the desired result) and the data stored in the database can be uncertain. Query results are then completely ordered with respect to these bipolar preferences, giving priority to constraints over wishes. Furthermore, we consider user preferences expressed on a domain of values which is not “flat”, but contains values that are more specific than others according to the “kind of” relation. These preferences are represented by specific fuzzy sets, called “Hierarchical Fuzzy Sets” and defined over a simple ontology. We propose a use of “Hierarchical Fuzzy Sets” for query enlargement purposes. The approach is illustrated on a real-world problem concerning the selection of optimal packaging material for fresh fruits and vegetables.

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

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Notes

  1. 1.

    Note that since \(\le _c\) and \(\le _w\) are complete pre-orderings, each constraint/wish has a well-defined rank.

  2. 2.

    Here, we adopt the usual notation \((x,y)\) for specifying fuzzy sets over symbolic variables, where \((x,y)\) means that modality \(x\) has membership value \(y\).

  3. 3.

    No preferences means here that all constraints (or wishes) have the same rank, i.e., are of equal importance.

  4. 4.

    A T-norm \(\top :\) [0, 1]\(^2\) to [0, 1] is an associative, commutative operator that has \(1\) for neutral element and \(0\) for absorbing element.

  5. 5.

    The shift loop (Lines 3-5) is there to keep the same indexing of subsets \({\fancyscript{T}}_j\)

  6. 6.

    A measure of the ability of a package to conduct gas fluxes.

References

  1. Benferhat, S., Dubois, D., Kaci, S., Prade, H.: Bipolar possibility theory in preference modelling: representation, fusion and optimal solutions. Inf. Fusion 7, 135–150 (2006)

    Article  Google Scholar 

  2. Bordogna, G., Pasi, G.: A fuzzy object oriented data model managing vague and uncertain information. Int. J. Intell. Syst. 14(6), SCI 3495 (1999)

    Google Scholar 

  3. Bosc, P., Lietard, L., Pivert, O.: Fuzzy theory techniques and applications in data-base management systems. In: Bosc, P., Kacprzyk, J. (eds.) Fuzziness in Database Management Systems, pp. 666–671. Academic Press, New York (1999)

    Google Scholar 

  4. Bosc, P., Lietard, L., Pivert, O.: Soft querying, a new feature for database management system. In: Proceedings DEXA’94 (Database and EXpert system Application), Lecture Notes in Computer Science, vol. 856, pp. 631–640. Springer-Verlag (1994)

    Google Scholar 

  5. Bosc, P., Pivert, O., Mokhtari, A., Lietard, L.: Extending relational algebra to handle bipolarity. In: Proceedings of the 2010 ACM Symposium on Applied Computing (SAC), pp. 1718–1722. Sierre, Switzerland, ACM, 22–26 March 2010

    Google Scholar 

  6. Bosc, P., Pivert, O.: About bipolar division operators. In: Flexible Query Answering Systems, 8th International Conference, FQAS 2009, Roskilde, Denmark, October 26–28, 2009. Proceedings. Lecture Notes in Computer Science, vol. 5822, pp. 572–582. Springer (2009)

    Google Scholar 

  7. Bosc, P., Pivert, O.: SQLf: a relational database language for fuzzy querying. IEEE Trans. Fuzzy Syst. 3(1), 1–17 (1995)

    Article  MathSciNet  Google Scholar 

  8. Bruno, N., Chaudhuri, S., Gravano, L.: Top-k selection queries over relational databases: Mapping strategies and performance evaluation. ACM Trans. Database Syst. 27(2), 153–187 (2002)

    Article  Google Scholar 

  9. Buche, P., Dibie-Barthelemy, J., Ibanescu, L., Soler, L.: Fuzzy web data tables integration guided by an ontological and terminological resource. IEEE Trans. Knowl. Data Eng. 24(4), 805–819 (2011)

    Google Scholar 

  10. Buche, P., Haemmerlé, O.: Towards a unified querying system of both structured and semi-structured imprecise data using fuzzy views. In: Proceedings of the 8th International Conference on Conceptual Structures, Lecture Notes in Artificial Intelligence, vol. 1867. pp. 207–220. Darmstadt, Germany, Springer-Verlag (August 2000)

    Google Scholar 

  11. Cacioppo, J.T., Gardner, W.L., Berntson, G.G.: Beyond bipolar conceptualizations and measures: the case of attitudes & evaluative space. Pers. Soc. Psychol. Rev. 1, 3–25 (1997)

    Article  Google Scholar 

  12. Charles, F., Sanchez, J., Gontard, N.: Modeling of active modified atmosphere packaging of endives exposed to several postharvest temperatures. J. Food Sci. 8, 443–448 (2005)

    Article  MATH  Google Scholar 

  13. Chomicki, J.: Preference formulas in relational queries. ACM Trans. Database Syst. 28(4), 427–466 (2003)

    Article  Google Scholar 

  14. Destercke, S., Dubois, D., Chojnacki, E.: Unifying practical uncertainty representations: I generalized p-boxes. Int. J. Approximate Reasoning 49(3), 664–677 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  15. Destercke, S., Dubois, D., Chojnacki, E.: Unifying practical uncertainty representations: II clouds. Int. J. Approximate Reasoning 49(3), 649–663 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  16. Destercke, S., Buche, P., Guillard, V.: A flexible bipolar querying approach with imprecise data and guaranteed results. Fuzzy Sets Syst. 169(1), 51–64 (2011)

    Article  MathSciNet  Google Scholar 

  17. Destercke, S., Guillard, V.: Interval analysis on non-linear monotonic systems as an efficient tool to optimise fresh food packaging. Comput. Electron. Agric. 79(2), 116–124 (2011)

    Article  Google Scholar 

  18. Dubois, D., Prade, H.: Bipolarity in flexible querying. In: Flexible Query Answering Systems, 5th International Conference, FQAS 2002, Copenhagen, Denmark, October 27–29, 2002, Proceedings. Lecture Notes in Computer Science, vol. 2522, pp. 174–182. Springer (2002)

    Google Scholar 

  19. Dubois, D., Prade, H.: Possibility Theory: An Approach to Computerized Processing of Uncertainty. Plenum Press, New York (1988)

    Google Scholar 

  20. Dubois, D., Prade, H.: Tolerant fuzzy pattern matching: an introduction. In: Bosc, P., Kacprzyk, J. (eds.) Fuzziness in Database Management Systems. Physica-Verlag (1995)

    Google Scholar 

  21. Dubois, D., Prade, H.: An overview of the asymmetric bipolar representation of positive and negative information in possibility theory. Fuzzy Sets Syst. 160, 1355–1366 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  22. Kießling, W., Köstler, G.: Preference SQL—design, implementation, experiences. In: VLDB Proceedings of 28th International Conference on Very Large Data Bases. pp. 990–1001. Morgan Kaufmann, Hong Kong, China, 20–23 August 2002

    Google Scholar 

  23. Klement, E., Mesiar, R., Pap, E.: Triangular Norms. Kluwer Academic Publisher, Dordrecht (2000)

    Google Scholar 

  24. Labreuche, C.: A general framework for explaining the results of a multi-attribute preference model. Artif. Intell. 175(7–8), 1410–1448 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  25. Mahajan, P., Oliveira, F., Montanez, J., Frias, J.: Development of user-friendly software for design of modified atmosphere packaging for fresh and fresh-cut produce. Innovative Food Sci. Emerg. Technol. 8, 84–92 (2007)

    Article  Google Scholar 

  26. Prade, H.: Lipski’s approach to incomplete information data bases restated and generalized in the setting of Zadeh’s possibility theory. Inf. Syst. 9(1), 27–42 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  27. Prade, H., Testemale, C.: Generalizing database relational algebra for the treatment of incomplete or uncertain information and vague queries. Inf. Sci. 34, 115–143 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  28. Thomopoulos, R., Buche, P., Haemmerlé, O.: Fuzzy sets defined on a hierarchical domain. IEEE Trans. Knowl. Data Eng. 18(10), 1397–1410 (2006)

    Article  Google Scholar 

  29. Tré, G.D., Caluwe, R.D.: A generalized object-oriented database model. In: Bordogna, G. Pasi, G. (eds.) Recent Research Issues on the Management of Fuzziness in Databases. Studies in Fuzziness and Soft computing, vol. 53, pp. 155–182. Physica-Verlag, Heidelberg, Germany (2000)

    Google Scholar 

  30. Tré, G.D., Zadrozny, S., Matthé, T., Kacprzyk, J., Bronselaer, A.: Dealing with positive and negative query criteria in fuzzy database querying. In: Flexible Query Answering Systems, 8th International Conference, FQAS 2009, Proceedings. Lecture Notes in Computer Science, vol. 5822, pp. 593–604. Roskilde, Denmark, Springer, 26–28 October 2009

    Google Scholar 

  31. Tré, G.D., Zadrozny, S., Bronselaer, A.: Handling bipolarity in elementary queries to possibilistic databases. IEEE Trans. Fuzzy Syst. 18, 599–612 (2010)

    Article  Google Scholar 

  32. Yager, R.: On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Trans. Syst. Man Cybern. 18, 183–190 (1988)

    Google Scholar 

  33. Zadeh, L.: The concept of a linguistic variable and its application to approximate reasoning-i. Inf. Sci. 8, 199–249 (1975)

    Article  MathSciNet  MATH  Google Scholar 

  34. Zadeh, L.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst. 1, 3–28 (1978)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/ 2007-2013) under the grant agreement FP7-265669-EcoBioCAP project.

Author information

Authors and Affiliations

  1. INRA IATE, 2, place Pierre Viala, F-34060 , Montpellier Cedex 02, France

    Patrice Buche & Rallou Thomopoulos

  2. LIRMM/CNRS-UM2/INRIA GRAPHIK, F-34392 , Montpellier, France

    Patrice Buche

  3. CNRS HEUDYASIC, Centre de recherches de Royallieu, F-60205 , Compiegne Cedex, France

    Sébastien Destercke

  4. UM2 IATE, cc 023 Pl. E. Bataillon, F-34095 , Montpellier, France

    Valérie Guillard

  5. IRIT-Melodi, Université Toulouse le Mirail, 5, Allées Antonio Machado, F-31058 , Toulouse Cedex 9, France

    Ollivier Haemmerlé

  6. LIRMM/CNRS-UM2/INRIA GRAPHIK, F-34392 , Montpellier, France

    Rallou Thomopoulos

Authors
  1. Patrice Buche
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sébastien Destercke
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Valérie Guillard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ollivier Haemmerlé
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rallou Thomopoulos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Patrice Buche .

Editor information

Editors and Affiliations

  1. IRISA/ENSSAT, Université de Rennes 1, Lannion Cedex, France

    Olivier Pivert

  2. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Sławomir Zadrożny

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Buche, P., Destercke, S., Guillard, V., Haemmerlé, O., Thomopoulos, R. (2014). Flexible Bipolar Querying of Uncertain Data Using an Ontology. In: Pivert, O., Zadrożny, S. (eds) Flexible Approaches in Data, Information and Knowledge Management. Studies in Computational Intelligence, vol 497. Springer, Cham. https://doi.org/10.1007/978-3-319-00954-4_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00954-4_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00953-7

  • Online ISBN: 978-3-319-00954-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation