Un systeme de traitement d'informations incompletes ou incertaines dans une base de donnees relationnelle

SIGLECNRS T 55859 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Une approche pour la gestion de l'imprecision et de l'incertitude dans les systemes d'information

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Fuzzy relational databases: Representational issues and reduction using similarity measures

International audienceUntil now, the idea of a fuzzy database has been investigated along different lines: Some authors have dealt with the imprecision of attribute values by modeling, using fuzzy similarity relations, the extent to which these values could be regarded as interchangeable. Others have used possibility distributions for representing fuzzily known or incompletely known attribute values. The first approach, which cannot accommodate incomplete information, is restated in the framework of rough sets extended to fuzzy relations. Besides, in the second one, similarity measures between attribute values can be introduced and computed; then a comparison of the two approaches is provided. The proposed similarity measure, based on a fuzzy Hausdorff distance, estimates the mismatch between two possibility distributions. From storage and query-evaluation points of view, it may be interesting to gather items having similar attribute values. Thus the similarity measures previously considered can be used for the reduction of the fuzzy database. When several items have sufficiently similar values for each attribute in a relation, the reduction is performed by taking for each attribute the union of these similar values. The consequences of the reduction process on query evaluation are studied

Generalizing database relational algebra for the treatment of incomplete or uncertain information and vague queries

International audienceThis paper deals with relational databases which are extended in the sense that fuzzily known values are allowed for attributes. Precise as well as partial (imprecise, uncertain) knowledge concerning the value of the attributes are represented by means of [0,1]-valued possibility distributions in Zadeh's sense. Thus, we have to manipulate ordinary relations on Cartesian products of sets of fuzzy subsets rather than fuzzy relations. Besides, vague queries whose contents are also represented by possibility distributions can be taken into account. The basic operations of relational algebra, union, intersection, Cartesian product, projection, and selection are extended in order to deal with partial information and vague queries. Approximate equalities and inequalities modeled by fuzzy relations can also be taken into account in the selection operation. Then, the main features of a query language based on the extended relational algebra are presented. An illustrative example is provided. This approach, which enables a very general treatment of relational databases with fuzzy attribute values, makes an extensive use of dual possibility and necessity measures

Application of possibility and necessity measures to documentary information retrieval

International audienc

Representation of soft constraints and fuzzy attribute values by means of possibility distributions in databases

International audienc

Weighted fuzzy pattern matching

International audienceThe fuzzy pattern matching technique has been developed in the framework of fuzzy set and possibility theory in order to take into account the imprecision and the uncertainty pervading values which have to be compared in a matching process. This technique has proved very useful for implementing patterns of approximate reasoning in expert system inference engines, and for designing retrieval systems capable of managing incomplete and fuzzy information data bases and vague queries. In this paper, the fuzzy pattern matching procedure is improved by introducing weights assessing the relative importance of atoms in the pattern. Matching indices are obtained using weighted versions of the minimum and maximum operations of fuzzy set theory. This approach is extended to the case of variable weights, and is related to aggregation schemes proposed by Yager when modeling soft quantified statements such as “most of the criteria must be met”. A notion of soft partial matching is thus modelled

In Search of a Modal System for Possibility Theory

International audienc

Extrapolation of fuzzy values from incomplete data bases

ArPlPT003 - This is a fully revised and extended revision of a paper “Analogical reasoning in fuzzy databases” presented at the 2nd International Fuzzy Systems Association Congress, Tokyo, 20–25 July, pp. 593–596 (1987)International audienceThis paper presents different approaches which enable a data base management system to obtain a plausible fuzzy estimate for an attribute value of an item for which the information is not explicitly stored in the data base. This can be made either by a kind of analogical reasoning from information about particular items or by means of expert rules which specify the (fuzzy) sets of possible values of the attribute under consideration, for various classes of items. Another kind of expert rules enables the system to compute an estimate from the attribute value of another item provided that, in other respects, this latter item sufficiently resembles the item, the value of which we are interested in; then these expert rules are used either for controlling the analogical reasoning process or for enlarging the scope of application of the first kind of expert rules. The different approaches are discussed in the framework of possibility theory

Data Fusion Problems in Intelligent Data Banks Interface

International audienceThe reported work has been motivated by different kinds of data fusion problems encountered in the design of an advanced interface for exploiting heterogeneous reliability parameter sources. The considered data fusion issues originate either in the aggregation of pieces of information obtained from different sources or in the treatment of fuzzy queries addressed to the interface. The aggregation problem is discussed both in the presence and the absence of confidence estimates for the pieces of information to De fused. The different combination problems are dealt with in the framework of possibility theory