Two kinds of fuzziness in attribute values of the fuzzy relational databases can be distinguished: One is that attribute values are possibility distributions, and the other is that there are resemblance relations in attribute domains. The fuzzy relational databases containing these two kinds of fuzz
Handling indefinite and maybe information in logical fuzzy relational databases
โ Scribed by Nan-Chen Hsieh
- Publisher
- John Wiley and Sons
- Year
- 2004
- Tongue
- English
- Weight
- 174 KB
- Volume
- 19
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
โฆ Synopsis
In this article, fuzzy set theory uses an extension of the classical logical relational database model. A logical fuzzy relational database model was developed with the aim of manipulating imprecise information and adding deduction capabilities to the database system. The essence of this work is the detailed discussion on fuzzy definite, fuzzy indefinite, and fuzzy maybe information and the development of an information theoretical approach of query evaluation on the logical fuzzy relational database. We define redundancies among fuzzy tuples and the operator of their removal. A complete set of fuzzy relational operations in relational algebra and the calculus of linguistically quantified propositions are included also.
๐ SIMILAR VOLUMES
There are two aspects of uncertainty: vagueness and ambiguity. This paper proposes IP (Implicit Predicate) to support both vagueness and ambiguity in fuzzy databases by allowing disjunctive fuzzy information. IP is basically a descriptor dedicated to an unknown value which turns out to be ambiguous