Research Information System
IEEE International Conference on Fuzzy Systems at the World Congress on Computational Intelligence (WCCI 98), Alaska, United States Of America, 4 - 09 May 1998, pp.1361-1366
Object-oriented and deductive database models are two different paradigms in database modeling. As has been pointed out by many researchers, [1], [6], [14], each of these data models has its shortcomings when dealing with database/knowledge-base applications. Therefore, it is believed that combining object-oriented concepts with those of deductive database modeling results in a powerful data model especially for knowledge-intensive applications. In these applications, it is important to model and manipulate complex objects and relationships with uncertain properties. This study introduces a fuzzy deductive object-oriented database model for representation and deduction of complex and fuzzy objects. Although various types of uncertainty, such as null, incomplete and fuzzy types are considered, we mainly focus on fuzzy types. Deduction is used to cope with complex relationships and to derive new information. In addition, the implementation of this model using Poplog environment is briefly described.