Automated database schema design using mined data dependencies

Data dependencies are used in database schema design to enforce the correctness of a database as well as to reduce redundant data. These dependencies are usually determined from the semantics of the attributes and are then enforced upon the relations. This article describes a bottom‐up procedure for...

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Bibliographic Details
Published in:Journal of the American Society for Information Science 1998-04, Vol.49 (5), p.455-470
Main Authors: Wong, S. K. M., Butz, C. J., Xiang, Y.
Format: Article
Language:English
Subjects:
Algorithms
Automation
Computer science
Data Analysis
Data Management
Data mining
Data Models
Data Organization
Database Design
Decomposition
Design
Information Systems
Information Technology
Knowledge discovery
Knowledge management
Machine learning
Mining
Probability
Prototypes
Reasoning
Relational data bases
Researchers
Semantics
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Summary:Data dependencies are used in database schema design to enforce the correctness of a database as well as to reduce redundant data. These dependencies are usually determined from the semantics of the attributes and are then enforced upon the relations. This article describes a bottom‐up procedure for discovering multivalued dependencies (MVDs) in observed data without knowing a priori the relationships among the attributes. The proposed algorithm is an application of the technique we designed for learning conditional independencies in probabilistic reasoning. A prototype system for automated database schema design has been implemented. Experiments were carried out to demonstrate both the effectiveness and efficiency of our method. © 1998 John Wiley & Sons, Inc.
ISSN:0002-8231
1097-4571
DOI:10.1002/(SICI)1097-4571(19980415)49:5<455::AID-ASI7>3.0.CO;2-M