Identifying Extended Entity-Relationship Object Structures in Relational Schemas
IEEE Transactions on Software Engineering
The design of relational databases
The design of relational databases
A survey of database design transformations based on the Entity-Relationship model
Data & Knowledge Engineering
Data mining: concepts and techniques
Data mining: concepts and techniques
The Clio project: managing heterogeneity
ACM SIGMOD Record
A Guided Tour of Relational Databases and Beyond
A Guided Tour of Relational Databases and Beyond
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
Discovering interesting inclusion dependencies: application to logical database tuning
Information Systems - Databases: Creation, management and utilization
Justification for Inclusion Dependency Normal Form
IEEE Transactions on Knowledge and Data Engineering
Discovery of Constraints and Data Dependencies in Databases (Extended Abstract)
ECML '95 Proceedings of the 8th European Conference on Machine Learning
Efficient Discovery of Functional Dependencies and Armstrong Relations
EDBT '00 Proceedings of the 7th International Conference on Extending Database Technology: Advances in Database Technology
Query Folding with Inclusion Dependencies
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies
ICDT '01 Proceedings of the 8th International Conference on Database Theory
Implementation of Two Semantic Query Optimization Techniques in DB2 Universal Database
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
VLDB '81 Proceedings of the seventh international conference on Very Large Data Bases - Volume 7
Samples for Understanding Data-Semantics in Relations
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Zigzag: a new algorithm for mining large inclusion dependencies in databases
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Experiences with student research at a primarily undergraduate institution
Journal of Computing Sciences in Colleges
Approximate matching of textual domain attributes for information source integration
Proceedings of the 2nd international workshop on Information quality in information systems
Semantic sampling of existing databases through informative Armstrong databases
Information Systems
Unary and n-ary inclusion dependency discovery in relational databases
Journal of Intelligent Information Systems
Functional dependency discovery via Bayes net analysis
MAMECTIS/NOLASC/CONTROL/WAMUS'11 Proceedings of the 13th WSEAS international conference on mathematical methods, computational techniques and intelligent systems, and 10th WSEAS international conference on non-linear analysis, non-linear systems and chaos, and 7th WSEAS international conference on dynamical systems and control, and 11th WSEAS international conference on Wavelet analysis and multirate systems: recent researches in computational techniques, non-linear systems and control
Heuristic strategies for the discovery of inclusion dependencies and other patterns
Journal on Data Semantics V
Proceedings of the 2004 European conference on Constraint-Based Mining and Inductive Databases
ACM SIGMOD Record
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Foreign keys form one of the most fundamental constraints for relational databases. Since they are not always defined in existing databases, algorithms need to be devised to discover foreign keys. One of the underlying problems is known to be the inclusion dependency (IND) inference problem. In this paper a new data mining algorithm for computing unary INDs is given. From unary INDs, we also propose a levelwise algorithmto discover all remaining INDs, where candidate INDs of size i + 1 are generated fromsatisfied INDs of size i, (i 0).An implementation of these algorithms has been achieved and tested against synthetic databases. Up to our knowledge, this paper is the first one to address in a comprehensive manner this data mining problem, from algorithms to experimental results.