Fuzzy Database Modeling

INTRODUCTION A major goal for database research has been the incorporation of additional semantics into the data model. Classical data models often suffer from their incapability of representing and manipulating imprecise and uncertain information that may occur in many real-world applications. Since the early 1980s, Zadeh's fuzzy logic (Zadeh, 1965) has been used to extend various data models. The purpose of introducing fuzzy logic in database modeling was to enhance the classical models such that uncertain and imprecise information can be represented and manipulated. This resulted in numerous contributions , mainly with respect to the popular relational model or to some related form of it. Also, rapid advances in computing power have brought opportunities for databases in emerging applications in CAD/CAM (Computer-Aided Design/Computer-Aided Manufacturing), multimedia, and geographic information systems (GIS). These applications characteristically require the modeling and manipulation of complex objects and semantic relationships. It proved that the object-oriented paradigm lends itself extremely well to the requirements. Because the classical relational database model and its extension of fuzziness do not satisfy the need of modeling complex objects with imprecision and uncertainty, many current researches have concentrated on fuzzy object-oriented database models to deal with complex objects and uncertain data together.