Fuzzy logic in data modeling: semantics, constraints, and database design
Fuzzy logic in data modeling: semantics, constraints, and database design
A relational model of data for large shared data banks
Communications of the ACM
Principles and Applications
Determining the membership values to optimize retrieval in a fuzzy relational database
Proceedings of the 44th annual Southeast regional conference
Spatial datbase feasibility for facial characterization using fuzzy logic queries
Proceedings of the 44th annual Southeast regional conference
Determining an optimal membership function based on community consensus in a fuzzy database system
Proceedings of the 44th annual Southeast regional conference
| Hi-index | 0.00 |
Most conventional databases in use today are based on the relational model. Values in a relation are taken from a finite set of strictly typed domain values. Each relation in the database represents a proposition and each record in a relation is a statement such that it evaluates to 'true' for that proposition (e.g., [3], [5]). It could be argued, however, that this required precision actually gives an insufficient representation of the world. The model is grounded in binary black-and-white but much of reality actually exists in shades of gray. As such, the conventional relational database model has limited usefulness.