International Journal of Man-Machine Studies
Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
Logical foundations of artificial intelligence
Logical foundations of artificial intelligence
An expert system for conceptual schema design: a machine learning approach
International Journal of Man-Machine Studies
A Uniform Approach to Constraint Satisfaction and Constraint Satisfiability in Deductive Databases
EDBT '88 Proceedings of the International Conference on Extending Database Technology: Advances in Database Technology
Abstracting Relational and Hierarchical Data with a Semantic Data Model
Proceedings of the Sixth International Conference on Entity-Relationship Approach
New Techniques for Data Reduction in a Database System for Knowledge Discovery Applications
Journal of Intelligent Information Systems
An Efficient Inductive Learning Method for Object-Oriented Database Using Attribute Entropy
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Decision table reduction in KDD: fuzzy rough based approach
Transactions on Rough Sets XI
Fuzzy rough set approach based classifier
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
| Hi-index | 0.00 |
A method for learning knowledge from a database is used to address the bottleneck of manual knowledge acquisition. An attempt is made to improve representation with the assistance of experts and from computer resident knowledge. The knowledge representation is described in the framework of a conceptual schema consisting of a semantic model and an event model. A concept classifies a domain into different subdomains. As a method of knowledge acquisition, inductive learning techniques are used for rule generation. The theory of rough sets is used in designing the learning algorithm. Examples of certain concepts are used to induce general specifications of the concepts called classification rules. The basic approach is to partition the information into equivalence classes and to derive conclusions based on equivalence relations. In a sense, what is involved is a data-reduction process, where the goal is to reduce a large database of information to a small number of rules describing the domain. This completely integrated approach includes user interface, semantics, constraints, representations of temporal events, induction, etc.