Negative Results for Equivalence Queries
Machine Learning
Learning Conjunctions of Horn Clauses
Machine Learning - Computational learning theory
Approximate inference of functional dependencies from relations
ICDT '92 Selected papers of the fourth international conference on Database theory
Read-twice DNF formulas are properly learnable
Information and Computation
Normalization and hierarchical dependencies in the relational data model
ACM Transactions on Database Systems (TODS)
Multivalued dependencies and a new normal form for relational databases
ACM Transactions on Database Systems (TODS)
A relational model of data for large shared data banks
Communications of the ACM
Learning Minimal Covers of Functional Dependencies with Queries
ALT '99 Proceedings of the 10th International Conference on Algorithmic Learning Theory
Horn Query Learning with Multiple Refinement
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Negative results on learning multivalued dependencies with queries
Information Processing Letters
| Hi-index | 5.23 |
Data dependencies play an important role in the design of relational databases. There is a strong connection between dependencies and some fragments of the propositional logic. In particular, functional dependencies are closely related to Horn formulas. Also, multivalued dependencies are characterized in terms of multivalued formulas. It is known that both Horn formulas and sets of functional dependencies are learnable in the exact model of learning with queries. Here we present an algorithm that learns a non-trivial subclass of multivalued formulas using membership and equivalence queries. Furthermore, a slight modification of the algorithm allows us to learn the corresponding subclass of multivalued dependencies.