Design by exmple: An application of Armstrong relations
Journal of Computer and System Sciences
Partition semantics for relations
Journal of Computer and System Sciences
The partition model: a deductive database model
ACM Transactions on Database Systems (TODS)
Identifying Extended Entity-Relationship Object Structures in Relational Schemas
IEEE Transactions on Software Engineering
The design of relational databases
The design of relational databases
Functional dependencies in relational databases: a lattice point of view
Discrete Applied Mathematics - Special issue on combinatorial problems in databases
Algorithms for inferring functional dependencies from relations
Data & Knowledge Engineering
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
An integrated approach to logical design of relational database schemes
ACM Transactions on Database Systems (TODS)
AutoAdmin “what-if” index analysis utility
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
The Asilomar report on database research
ACM SIGMOD Record
Mining the most interesting rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Horn clauses and database dependencies
Journal of the ACM (JACM)
On the Structure of Armstrong Relations for Functional Dependencies
Journal of the ACM (JACM)
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
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
Efficient Discovery of Functional and Approximate Dependencies Using Partitions
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Discovery of "Interesting" Data Dependencies from a Workload of SQL Statements
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mining Bases for Association Rules Using Closed Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Efficient Algorithms for Mining Inclusion Dependencies
EDBT '02 Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology
FUN: An Efficient Algorithm for Mining Functional and Embedded Dependencies
ICDT '01 Proceedings of the 8th International Conference on Database Theory
An Axiomatic Approach to Defining Approximation Measures for Functional Dependencies
ADBIS '02 Proceedings of the 6th East European Conference on Advances in Databases and Information Systems
DaWaK '01 Proceedings of the Third International Conference on Data Warehousing and Knowledge Discovery
Improving Query Evaluation with Approximate Functional Dependency Based Decompositions
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
Samples for Understanding Data-Semantics in Relations
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
On Monotone Data Mining Languages
DBPL '01 Revised Papers from the 8th International Workshop on Database Programming Languages
Deciding on the Equivalence of a Relational Schema and and Object-Oriented Schema
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
Fast Discovery of Minimal Sets of Attributes Functionally Determining a Decision Attribute
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
FUN: Fast Discovery of Minimal Sets of Attributes Functionally Determining a Decision Attribute
Transactions on Rough Sets IX
On Matrix Representations of Participation Constraints
ER '09 Proceedings of the ER 2009 Workshops (CoMoL, ETheCoM, FP-UML, MOST-ONISW, QoIS, RIGiM, SeCoGIS) on Advances in Conceptual Modeling - Challenging Perspectives
CRIUS: user-friendly database design
Proceedings of the VLDB Endowment
The agree concept lattice for multidimensional database analysis
ICFCA'11 Proceedings of the 9th international conference on Formal concept analysis
Interactively eliciting database constraints and dependencies
CAiSE'11 Proceedings of the 23rd international conference on Advanced information systems engineering
Towards a parallel approach for incremental mining of functional dependencies on multi-core systems
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Extending functional dependency to detect abnormal data in RDF graphs
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
A parallel algorithm for computing borders
Proceedings of the 20th ACM international conference on Information and knowledge management
On the existence of armstrong data trees for XML functional dependencies
FoIKS'10 Proceedings of the 6th international conference on Foundations of Information and Knowledge Systems
ICFCA'05 Proceedings of the Third international conference on Formal Concept Analysis
Proceedings of the 21st ACM international conference on Information and knowledge management
Using data samples in validating data models
International Journal of Knowledge Engineering and Soft Data Paradigms
| Hi-index | 0.01 |
In this paper, we propose a new efficient algorithm called Dep-Miner for discovering minimal non-trivial functional dependencies from large databases. Based on theoretical foundations, our approach combines the discovery of functional dependencies along with the construction of real-world Armstrong relations (without additional execution time). These relations are small Armstrong relations taking their values in the initial relation. Discovering both minimal functional dependencies and real-world Armstrong relations facilitate the tasks of database administrators when maintaining and analyzing existing databases. We evaluate Dep-Miner performances by using a new benchmark database. Experimental results show both the efficiency of our approach compared to the best current algorithm (i.e. Tane), and the usefulness of real-world Armstrong relations.