An Extended Relational Data Model For Probabilistic Reasoning
Journal of Intelligent Information Systems
The Relational Structure of Belief Networks
Journal of Intelligent Information Systems
A note on approximation measures for multi-valued dependencies in relational databases
Information Processing Letters
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
Improving Query Evaluation with Approximate Functional Dependency Based Decompositions
BNCOD 19 Proceedings of the 19th British National Conference on Databases: Advances in Databases
On Information-Theoretic Measures of Attribute Importance
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Why is the snowflake schema a good data warehouse design?
Information Systems
An information-theoretic approach to normal forms for relational and XML data
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Granular computing using information tables
Data mining, rough sets and granular computing
On approximation measures for functional dependencies
Information Systems - Special issue: ADBIS 2002: Advances in databases and information systems
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
An information-theoretic approach to normal forms for relational and XML data
Journal of the ACM (JACM)
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Browsing mixed structured and unstructured data
Information Processing and Management: an International Journal
On redundancy vs dependency preservation in normalization: an information-theoretic study of 3NF
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
XML design for relational storage
Proceedings of the 16th international conference on World Wide Web
The implication problem for measure-based constraints
Information Systems
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Information Sciences: an International Journal
A correctness criterion for schema dominance centred on the notion of 'information carrying'
CEA'09 Proceedings of the 3rd WSEAS international conference on Computer engineering and applications
An information-theoretic analysis of worst-case redundancy in database design
ACM Transactions on Database Systems (TODS)
Browsing mixed structured and unstructured data
Information Processing and Management: an International Journal
WSEAS Transactions on Information Science and Applications
A measurement theory view on the granularity of partitions
Information Sciences: an International Journal
An Axiomatic Approach to the Roughness Measure of Rough Sets
Fundamenta Informaticae
XSym'07 Proceedings of the 5th international conference on Database and XML Technologies
Entropy measures and granularity measures for set-valued information systems
Information Sciences: an International Journal
Information interpretation of knowledge granularity
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
| Hi-index | 0.00 |
Database design is based on the concept of data dependency, which is the interrelationship between data contained in various sets of attributes. In particular, functional, multivalued and acyclic join, dependencies play an essential role in the design of database schemas. The basic definition of an information metric and how this notion can be used in relational database are discussed in this paper. We use Shannon entropy as an information metric to quantify the information associated with a set of attributes. Thus, we prove that data dependencies can be formulated in terms of entropies. These formulas make the numerical computation and testing of data dependencies feasible. Among the different types of data dependencies, the acyclic join dependency is most important to the design of a relational database schema. The acyclic join dependency, with multivalued dependency as a special case, impose a constraint on the information-preserving decomposition of a relation. It is interesting that this constraint on a relation is similar to Gibbs' condition for separating physical systems in statistical mechanics. They both assert that entropy is preserved during the decomposition process. That is, the entropies of the corresponding set of attributes must satisfy the inclusion-exclusion identity.