Name
Abstract | ||
|---|---|---|
We investigate the impact of uncertainty on relational database schema design. Uncertainty is modeled qualitatively by assigning to tuples a degree of possibility with which they occur, and assigning to functional dependencies a degree of certainty which says to which tuples they apply. A design theory is developed for possibilistic functional dependencies, including efficient axiomatic and algorithmic characterizations of their implication problem. Naturally, the possibility degrees of tuples result in a scale of different degrees of data redundancy. Scaled versions of the classical syntactic Boyce-Codd and Third Normal Forms are established and semantically justified in terms of avoiding data redundancy of different degrees. Classical decomposition and synthesis techniques are scaled as well. Therefore, possibilistic functional dependencies do not just enable designers to control the levels of data integrity and losslessness targeted but also to balance the classical trade-off between query and update efficiency. Extensive experiments confirm the efficiency of our framework and provide original insight into relational schema design. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2983323.2983801 | ACM International Conference on Information and Knowledge Management |
Keywords | Field | DocType |
Axioms,Boyce-Codd normal form,Data redundancy,Implication problem,Third normal form,Possibility theory | Data mining,Superkey,Relational database,Computer science,Tuple,Uncertain data,Functional dependency,Data integrity,Third normal form,Boyce–Codd normal form | Conference |
Citations | PageRank | References |
6 | 0.41 | 19 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sebastian Link | 1 | 185 | 12.50 |
| Henri Prade | 2 | 10549 | 1445.02 |