Modeling Fuzzy Information in the EER and Nested Relational Database Models

Abstract

A major goal for database research has been the incorporation of additional semantics into database models. It is recognized that the relational database model has semantic and structured drawbacks when it comes to modeling some emerging applications such as computer aided design (CAD), geographical information systems (GIS), and artificial intelligence. In response to this problem, some attempts to relax the first normal form (1NF) limitation, which is the most fundamental normalization constraint in the relational databases, are made and one kind of data model, called non-first normal (or nested) relational database model, has been introduced. In common sense, the nested relational database model means that attribute values in the relational instances are either atomic or set-valued and even relations themselves. In addition, the next generation of database models takes the form of rich data models such as the object-oriented database model and the semantic (conceptual) data models. In real world applications, information is often vague or ambiguous. Therefore, different kinds of imperfect information have been extensively introduced into relational databases [8, 18, 25, 26]. However, the classical relational database model and its extensions with imprecision and uncertainty does not satisfy the need of modeling complex objects with imprecise and uncertain information. So, many researches have concentrated on conceptual data models [10, 31, 38] and object-oriented databases (OODB) [2, 12-17, 22] to deal with complex objects and uncertain data together. It should be pointed out that, being the extension of the relational database model, the nested relational database model is able to handle complex-valued attributes and may be better suitable to some complex applications (e.g., office automation systems, information retrieval systems and expert database systems [33]). In [33], an extended nested relational database model (also known as an NF data model)