The characterization of branching dependencies
Discrete Applied Mathematics - Special issue on combinatorial problems in databases
Approximate inference of functional dependencies from relations
ICDT '92 Selected papers of the fourth international conference on Database theory
Towards on-line analytical mining in large databases
ACM SIGMOD Record
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Selecting and materializing horizontally partitioned warehouse views
Data & Knowledge Engineering
MCSE: Microsoft SQL Server 2000 Database Design and Implementation Training Kit
MCSE: Microsoft SQL Server 2000 Database Design and Implementation Training Kit
Database Systems: The Complete Book
Database Systems: The Complete Book
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
View selection using randomized search
Data & Knowledge Engineering
Data & Knowledge Engineering
Improving Query Evaluation with Approximate Functional Dependency Based Decompositions
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
An Entropy-based Approach to Visualizing Database Structure
Proceedings of the IFIP TC2/WG2.6 Sixth Working Conference on Visual Database Systems: Visual and Multimedia Information Management
On approximation measures for functional dependencies
Information Systems - Special issue: ADBIS 2002: Advances in databases and information systems
Materialization of fragmented views in multidimensional databases
Data & Knowledge Engineering
Mining approximate functional dependencies and concept similarities to answer imprecise queries
Proceedings of the 7th International Workshop on the Web and Databases: colocated with ACM SIGMOD/PODS 2004
SQL-based discovery of exact and approximate functional dependencies
Working group reports from ITiCSE on Innovation and technology in computer science education
Efficient incremental maintenance of data cubes
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Database dependency discovery: a machine learning approach
AI Communications
Graphs, Networks and Algorithms
Graphs, Networks and Algorithms
Constraint acquisition for Entity-Relationship models
Data & Knowledge Engineering
| Hi-index | 0.00 |
The discovery of dependencies between attributes in databases is an important problem in data mining, and can be applied to facilitate future decision-making. In the present paper some properties of the branching dependencies are examined. We define a minimal branching dependency and we propose an algorithm for finding all minimal branching dependencies between a given set of attributes and a given attribute in a relation of a database. Our examination of the branching dependencies is motivated by their application in a database storing realized sales of products. For example, finding out that arbitrary p products have totally attracted at most q new users can prove to be crucial in supporting the decision making. In addition, we also consider the fractional and the fractional branching dependencies. Some properties of these dependencies are examined. An algorithm for finding all fractional dependencies between a given set of attributes and a given attribute in a database relation is proposed. We examine the general case of an arbitrary relation, as well as a particular case where the problem of discovering the fractional dependencies is considerably simplified.