Skip to main content
SpringerLink
Log in

Information Systems Uncertainty Design and Implementation Combining: Rough, Fuzzy, and Intuitionistic Approaches

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

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

Abstract

There are a number of alternative techniques for dealing with uncertainty. Here we discuss rough set, fuzzy rough set, and intuitionistic rough set approaches and how to incorporate uncertainty management using them in the relational database model. The impacts of rough set techniques on fundamental database concepts such as functional dependencies and information theory are also considered.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
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

References

  1. Atanassov, K.: Intuitionistic Fuzzy Sets. Fuzzy Sets Syst. 20, 87–96 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  2. Atanassov, K.: On Intuitionistic Fuzzy Sets Theory. Springer-Verlag (2012)

    Google Scholar 

  3. Beaubouef, T., Petry F.: Rough Querying of Crisp Data in Relational Databases. Proceedings of Third International Workshop on Rough Sets and Soft Computing (RSSC’94), pp. 368–375, San Jose, California (1994)

    Google Scholar 

  4. Beaubouef, T., Petry, F.: Fuzzy Set Quantification of Roughness in a Rough Relational Database Model. Proceedings of Third IEEE International Conference on Fuzzy Systems, pp. 172–177, Orlando, Florida (1994)

    Google Scholar 

  5. Beaubouef, T., Petry, F.: Fuzzy rough set techniques for uncertainty processing in a relational database. Int. J. Intell. Syst. 15, 389–424 (2000)

    Article  MATH  Google Scholar 

  6. Beaubouef, T., Petry F.: A rough set foundation for spatial data mining involving vague regions. Proceedings of FUZZ-IEEE’02, pp. 767–772, Honolulu, Hawaii (2002)

    Google Scholar 

  7. Beaubouef, T., Petry F.: Rough Functional Dependencies, 2004 Multiconferences: International Conference On Information and Knowledge Engineering (IKE’04), pp. 175–179, Las Vegas (2004)

    Google Scholar 

  8. Beaubouef, T., Petry, F.: Uncertainty modeling for database design using intuitionistic and rough set theory. Int. J. Intell. Fuzzy Syst. 20(3), 105–117 (2009)

    MATH  Google Scholar 

  9. Beaubouef, T., Petry F.: Imprecise Database Security and Information Measures., International J. Comput. Intell.: Theory Pract. 5(2), 61–7 (2010)

    Google Scholar 

  10. Beaubouef, T., Petry, F., Arora, G.: Information-theoretic measures of uncertainty for rough sets and rough relational databases. Inf. Sci. 109, 185–195 (1998)

    Article  Google Scholar 

  11. Beaubouef, T., Petry, F., Buckles, B.: Extension of the relational database and its algebra with rough set techniques. Comput. Intell. 11, 233–245 (1995)

    Article  Google Scholar 

  12. Bhandari, D., Pal, N.R.: Some new information measures for fuzzy sets. Inform. Sci. 67, 209–228 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  13. Bosc, P., Gailbourg, M., Hamlin, G.: Fuzzy querying with SQL: extensions and implementation aspects. Fuzzy Sets Syst. 28(3), 333–339 (1988)

    Article  MATH  Google Scholar 

  14. Bosc, P., Pivert, O.: Some approaches for relational databases flexible querying. J. Intell. Inf. Syst. 1, 323–354 (1992)

    Article  Google Scholar 

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

    Article  Google Scholar 

  16. Buckles, B., Petry, F.: A fuzzy model for relational databases. Int. J. Fuzzy Sets Syst. 7, 213–226 (1982)

    Article  MATH  Google Scholar 

  17. Buckles, B., Petry, F.: Security and Fuzzy Databases, Proceedings of 1982 IEEE International Conference on Cybernetics and Society, pp. 622–625, Seattle WA (1982)

    Google Scholar 

  18. Buckles, B., Petry, F.: Information-theoretical characterization of fuzzy relational databases. IEEE Trans. Syst. Man Cybern. 13, 74–77 (1983)

    Article  Google Scholar 

  19. Chanas, S., Kuchta, D.: Further remarks on the relation between rough and fuzzy sets. Fuzzy Sets Syst. 47, 391–394 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  20. Codd, E.: A relational model of data for large shared data banks. Commun. ACM 13(6), 377–387 (1970)

    Article  MATH  Google Scholar 

  21. de Luca, A., Termini, S.: A definition of a non-probabilistic entropy in the setting of fuzzy set theory. Inf. Control 20, 301–312 (1972)

    Article  MATH  Google Scholar 

  22. Denning, D.: Secure statistical databases with random sample queries. Trans. Database Syst. 5(3), 291–315 (1980)

    Article  MATH  Google Scholar 

  23. Dubois, D., Prade, H.: Putting rough sets and fuzzy sets together. In: Slowinski, R. (ed.) Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory. Kluwer Academic Publishers, Boston (1992)

    Google Scholar 

  24. Dubois, D., Godo, L., Prade, H., Esteva, F.: An information-based discussion of vagueness. In: Cohen, H., Lefebvre, C. (eds.) Handbook of Categorization in Cognitive Science, Chap. 40, pp. 892–913 , Elsevier (2005)

    Google Scholar 

  25. Elmasri, R., Navathe, S.: Fundamentals of Database Systems, 5th edn. Pearson/Addison Wesley (2007)

    Google Scholar 

  26. Fung, K., Lam, C.: The database entropy concept and its application to the data allocation problem. INFOR 18(4), 354–363 (1980)

    Google Scholar 

  27. Klir, G., Folger, T.: Fuzzy Sets, Uncertainty, and Information. Prentice Hall, Englewood Cliffs NJ (1988)

    MATH  Google Scholar 

  28. Ligeza, A.: Granular Sets and Granular Relation. Intelligent Information Systems, pp. 331–340, Physica Verlag (2002)

    Google Scholar 

  29. Lin, T.Y.: Topological and fuzzy rough sets. In: Slowinski, R. (ed.) Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory, pp. 287–304. Kluwer Academic Publishers, Boston (1992)

    Chapter  Google Scholar 

  30. Makinouchi, A.: A Consideration on normal form of not-necessarily normalized relation in the relational data model. Proceedings of the 3rd International Conference on VLDB, pp. 447–453 (1977)

    Google Scholar 

  31. Motro, A., Marks, D., Jajodia, S.: Aggregation in relational databases: controlled disclosure of sensitive information. In: Proceedings of ESORICS 94, Third European Symposium on Research in Computer Security. Lecture Notes in Computer Science, vol. 875, pp. 431–445, Brighton, UK, Springer-Verlag (1994)

    Google Scholar 

  32. Nanda, S., Majumdar, S.: Fuzzy rough sets. Fuzzy Sets Syst. 45, 157160 (1992)

    Article  MathSciNet  Google Scholar 

  33. Nilsson, N.: Probabilistic Logic. Artif. Intell. 28(1), 71–87 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  34. Ola, A., Ozsoyoglu, G.: Incomplete relational database models based on intervals. IEEE Trans. Knowl. Data Eng. 5, 293–308 (1993)

    Article  Google Scholar 

  35. Pawlak, Z.: Rough sets. Int. J. Comput. Inform. Sci. 11, 341–356 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  36. Pawlak, Z.: Rough sets and fuzzy sets. Fuzzy Sets Syst. 17, 99–102 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  37. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers, Norwell, MA (1991)

    Book  MATH  Google Scholar 

  38. Prade, H., Testemale, T.: Generalizing database relational algebra for the treatment of incomplete/uncertain information and vague queries. Inform. Sci. 34, 115–143 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  39. Quinlan, J.: Induction of decision trees. Mach. Learn. 1, 81–106 (1986)

    Google Scholar 

  40. Randell, D., Cui, Z., Cohn, A.: An interval logic for space based on connection. In: Proceedings of ECAI, pp. 394–398 (1992)

    Google Scholar 

  41. Shannon, C.: The mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423 (1948)

    Google Scholar 

  42. Shenoi, S., Melton, A., Fan, L.: Functional dependencies and normal forms in the fuzzy relational database model. Inf. Sci. 60, 1–28 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  43. Srinivasan, P.: The importance of rough approximations for information retrieval. Int. J. Man Mach. Stud. 34, 657–671 (1991)

    Article  Google Scholar 

  44. Szmidt, E., Kacprzyk, J.: On distances between intuitionistic fuzzy sets. Fuzzy Sets Syst. 114, 505–518 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  45. Szmidt, E., Kacprzyk, J.: Entropy for intuitionistic fuzzy sets. Fuzzy Sets Syst. 118, 467–477 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  46. Umano, M.: FREEDOM-O: a fuzzy database system. In: Gupta, M., Sanchez, E. (eds.) Fuzzy Information and Studies in Fuzziness Series, pp. 339–347. Physica-Verlag, Heidelberg, Decision Processes, North-Holland (1982)

    Google Scholar 

  47. Wygralak, M.: Rough sets and fuzzy sets-some remarks on interrelations. Fuzzy Sets Syst. 29, 241–243 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  48. Yao, P.: Fuzzy rough set and information entropy based feature selection for credit scoring. Proc. 6th Int. Conf. Fuzzy Syst. Knowl. Disc. 6, 247–251 (2009)

    Google Scholar 

  49. Yao, Y.: Semantics of Fuzzy Sets in Rough Set Theory. T. Rough Sets II, 297–318 (2004)

    Google Scholar 

  50. Zadeh, L.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  51. Zadeh, L.A.: Possibility theory and soft data analysis. In: Cobb, L., Thrall, R.M. (eds.) Mathematical Frontiers of the Social and Policy Sciences. Westview, Boulder, CO., pp. 69–129 (1981)

    Google Scholar 

  52. Zemankova, M., Kandel, A.: Implementing Imprecision in Information Systems. Inf. Sci. 37, 107–141 (1985)

    Google Scholar 

Download references

Acknowledgments

This work was supported by the Naval Research Laboratory’s Base Program, Program Element No. 0602435N

Author information

Authors and Affiliations

  1. Southeastern Louisiana University, Hammond, Louisiana, USA

    Theresa Beaubouef

  2. Naval Research Lab, Stennis Space Center, Mississippi, USA

    Frederick Petry

Authors
  1. Theresa Beaubouef
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Frederick Petry
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Frederick Petry .

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

Beaubouef, T., Petry, F. (2014). Information Systems Uncertainty Design and Implementation Combining: Rough, Fuzzy, and Intuitionistic Approaches. 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_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00954-4_7

  • 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