×

zbMATH — the first resource for mathematics

Extending the relational model to deal with probabilistic data. (English) Zbl 0969.68630
Summary: 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.
MSC:
68U99 Computing methodologies and applications
68P15 Database theory
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] Klir G J, Folger T A. Fuzzy Sets, Uncertainty, and Information. Prentice Hall, Englewood Cliffs, N.J., 1988. · Zbl 0675.94025
[2] Codd E F. Extending the database relational model to capture more meaning.ACM Trans. Database System, 1979, 4(4): 397–434.
[3] Date C J. Relational Database: Selected Writings. Addison-Wesley, Reading, Mass., 1986. · Zbl 0625.68071
[4] Maier D. The Theory of Relational Databases. Computer Science Press, Rockville, MD, 1983. · Zbl 0519.68082
[5] Grant J. Partial values in a tabular database model.Information Processing Letters, 1979, 9(2): 97–99. · Zbl 0417.68084
[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. · Zbl 05109385
[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] Buckles B P, Petry F E. Extending the fuzzy database with fuzzy numbers.Inf. Sci. (New York), 1984, 34: 145–155. · Zbl 0555.68069
[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. · Zbl 0552.68082
[10] Zemankova M, Kandel A. Implementing imprecision in information systems.Inf. Sci. (New York), 1985, 37: 107–141. · Zbl 0583.68053
[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] Zadeh L A. Fuzzy sets.Information and Control, 1965, 8(3): 338–353. · Zbl 0139.24606
[13] He X G. Data models of the fuzzy relational databases.Chinese Journal of Computers, 1989, 12(2): 120–126.
[14] He X G. Semantic distance and fuzzy user’s view in fuzzy databases.Chinese Journal of Computers, 1989, 12(10): 757–764.
[15] Cavallo R, Pittarelli M. The theory of probabilistic databases. InProceedings of the 13th VLDB Conference, Brighton, UK, 1987, pp.71–81.
[16] Barbara D, Garcia-molina H, Porter D. The management of probabilistic data.IEEE Trans. Knowl. Data Eng., 1992, 4(5): 487–502. · Zbl 05109620
[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] Dey D, Sarkar S A. Probabilistic relational model and algebra.ACM Trans. Database System, 1996, 21(3): 339–369.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.