Ria Vandenberghe

UFO: uncertainty and fuzziness in an object-oriented model

The authors present a method for coping with the uncertainty and fuzziness that cause problems in handling information. As these two concepts carry different semantic meanings, they distinguish between them by representing fuzzy information as conjunctive fuzzy sets and uncertainty by means of generalized fuzzy sets. An object-oriented methodology is chosen because it offers an excellent framework for handling uncertainty in a way completely transparent to the user. This treatment of uncertainty in a fuzzy object-oriented environment is well-suited to databases; hence examples from this field are selected. Genealogical databases, where uncertain information is very common, and where information is continuously updated, are used as a frame of reference. The proposed model also allows storage of as much information about uncertain objects as possible.<<ETX>>

Some practical aspects of fuzzy database techniques: an example

Abstract Basically there are two approaches for dealing with incomplete or imprecise information in the framework of (relational) databases. Buckles and Petry introduced fuzzy similarity relations in order to estimate to what extent possible values of an attribute can be regarded as interchangeable. In the approach of Dubois. Prade and Testemale possibility distributions were used to represent all possible kinds of incompletely or fuzzily known values. This paper describes the application of a combination of both techniques. We focus on the very specific domain of criminal investigation, especially on criminal identification by means of a personal description. However, the developed method can be applied to a lot of other domains, where a similar sort of fuzziness and uncertainty shows up. For most attributes the fuzzy values are considered as primitive notions. Each domain is provided with a sup-W-transitive likeness relation in order to represent an existing kind of overlapping between the possible fuzzy values. Moreover, in order to restrict the number of attributes we allow multivalued ones: their values are represented as possibility distributions on the power class of the domain. The pattern-matching process uses a Prade-Testemale-like technique based on possibility distributions.

Integrating Fuzziness in Database Models

In this paper we propose a way of integrating fuzziness and uncertainty in three database models: the relational database model, an extended entity-relationship model and an object-oriented database model. For this, we rely upon the notion of fuzzy truth value, defined as a fuzzy set on {true, false}, and on the corresponding fuzzy logic, of which simplicity is its strength.

Modelling vague lexical time expressions by means of fuzzy set theory

Abstract On the basis of some large scale inquiries into the nature of time expressions in natural language, in which informants were asked to indicate sharp (crisp) and closed time intervals for a range of linguistic expressions, several models of representing vague lexical time intervals by means of fuzzy set theory are discussed. These models primarily depend on the type of expressions used, and thus take into account the complex heterogeneous semantics of time indications.