Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Extending the relational model to deal with probabilistic data

  • 36 Accesses

Abstract

According to the soundness and completeness of information in databases, the expressive form and the semantics of incomplete information are discussed in this paper. On the basis of the discussion, the current studies on incomplete data in relational databases are reviewed. In order to represent stochastic uncertainty in most general sense in the real world, probabilistic data are introduced into relational databases. An extended relational data model is presented to express and manipulate probabilistic data and the operations in relational algebra based on the extended model are defined in this paper.

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

References

  1. [1]

    Klir G J, Folger T A. Fuzzy Sets, Uncertainty, and Information. Prentice Hall, Englewood Cliffs, N.J., 1988.

  2. [2]

    Codd E F. Extending the database relational model to capture more meaning.ACM Trans. Database System, 1979, 4(4): 397–434.

  3. [3]

    Date C J. Relational Database: Selected Writings. Addison-Wesley, Reading, Mass., 1986.

  4. [4]

    Maier D. The Theory of Relational Databases. Computer Science Press, Rockville, MD, 1983.

  5. [5]

    Grant J. Partial values in a tabular database model.Information Processing Letters, 1979, 9(2): 97–99.

  6. [6]

    DeMichiel L G. Resolving database incompatibility: An approach to performing relational operations over mismatched domains.IEEE Trans. Knowledge and Data Engineering, 1989, 1(4): 485–493.

  7. [7]

    Buckles B P, Petry F E. Information-theoretical characterisation of fuzzy relational databases.IEEE Trans. Syst. Man Cybern., 1983, 13(1): 74–77.

  8. [8]

    Buckles B P, Petry F E. Extending the fuzzy database with fuzzy numbers.Inf. Sci. (New York), 1984, 34: 145–155.

  9. [9]

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

  10. [10]

    Zemankova M, Kandel A. Implementing imprecision in information systems.Inf. Sci. (New York), 1985, 37: 107–141.

  11. [11]

    Raju K V S V N, Majumdar A K. Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems.ACM Trans. Database System, 1988, 13(2): 129–166.

  12. [12]

    Zadeh L A. Fuzzy sets.Information and Control, 1965, 8(3): 338–353.

  13. [13]

    He X G. Data models of the fuzzy relational databases.Chinese Journal of Computers, 1989, 12(2): 120–126.

  14. [14]

    He X G. Semantic distance and fuzzy user’s view in fuzzy databases.Chinese Journal of Computers, 1989, 12(10): 757–764.

  15. [15]

    Cavallo R, Pittarelli M. The theory of probabilistic databases. InProceedings of the 13th VLDB Conference, Brighton, UK, 1987, pp.71–81.

  16. [16]

    Barbara D, Garcia-molina H, Porter D. The management of probabilistic data.IEEE Trans. Knowl. Data Eng., 1992, 4(5): 487–502.

  17. [17]

    Tseng F S C, Chen A L P, Yang W P. Answering heterogeneous database queries with degrees of uncertainty.Distributed and Parallel Databases: An International Journal, 1993, 1(3): 281–302.

  18. [18]

    Dey D, Sarkar S A. Probabilistic relational model and algebra.ACM Trans. Database System, 1996, 21(3): 339–369.

Download references

Author information

Correspondence to Zongmin Ma.

Additional information

MA Zongmin received his M.Eng. degree from the Northeast Heavy Machinery Institute (now Yanshan University, Qinhuandao, China) in 1992. His current research interests include imprecise and uncertain information modeling in conceptual data model and logical databases (relational databases and object-oriented databases), data fusion and databases integration, data mining, fuzzy reasoning, temporal and spatial databases, and engineering databases. He has published over 10 papers in international journals and international conference proceedings.

ZHANG W.J. received his Ph.D degree from the Delft University of Technology, the Netherlands in 1994. Dr. Zhang is currently an Associate Professor in the University of Saskatchewan, Canada. His research interests include information modeling for design and manufacturing, intelligent production systems.

MA W.Y. received his Ph.D. degree from the Katholieke University Leuven, Belgium in 1994. Dr. Ma is currently an Assistant Professor in the City University of Hong Kong. His research interests include CAD/CAM, virtual reality for product design, rapid prototyping and manufacturing, and reverse engineering.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Ma, Z., Zhang, W.J. & Ma, W.Y. Extending the relational model to deal with probabilistic data. J. Comput. Sci. & Technol. 15, 230–240 (2000). https://doi.org/10.1007/BF02948810

Download citation

Keywords

  • incomplete information
  • uncertain information
  • extended relational model
  • probabilistic data
  • relational algebra